From 786b465dc632f94e6e22c16d37a9f4b253512fcd Mon Sep 17 00:00:00 2001 From: Robert Date: Fri, 17 Nov 2023 13:17:43 +0100 Subject: [PATCH 1/4] - added research files to correct folders - split up the perception/planning file into two seperate files and put them into the correct folders - added a research_asset folder inside the 00_asset folder - created links to each added file inside the corresponding Readme files - added sprint_01 to dev talks folder --- .../research_assetes/messages_paf21_2.png | Bin 0 -> 188877 bytes doc/00_assets/research_assetes/mpc.png | Bin 0 -> 64286 bytes .../research_assetes/pure_pursuit.png | Bin 0 -> 82158 bytes .../standard_routine_paf21_2.png | Bin 0 -> 107841 bytes .../research_assetes/stanley_controller.png | Bin 0 -> 16604 bytes ...paf21_1_Acting.md => 03_paf21_1_Acting.md} | 0 .../04_research_Acting_Pylot_and_PAF21_2.md | 313 ++++++++++++++++++ ...toware_acting.md => 05_autoware_acting.md} | 0 doc/03_research/01_acting/Readme.md | 5 + .../05_Research_PAF21-Perception.md} | 27 -- doc/03_research/02_perception/Readme.md | 3 +- .../03_planning/09_Research_Pylot_Planning.md | 28 ++ doc/03_research/03_planning/Readme.md | 1 + .../{ => dev_talks_paf22}/sprint_4.md | 0 .../{ => dev_talks_paf22}/sprint_5.md | 0 doc/08_dev_talks/dev_talks_paf23/sprint_1.md | 37 +++ 16 files changed, 386 insertions(+), 28 deletions(-) create mode 100644 doc/00_assets/research_assetes/messages_paf21_2.png create mode 100644 doc/00_assets/research_assetes/mpc.png create mode 100644 doc/00_assets/research_assetes/pure_pursuit.png create mode 100644 doc/00_assets/research_assetes/standard_routine_paf21_2.png create mode 100644 doc/00_assets/research_assetes/stanley_controller.png rename doc/03_research/01_acting/{paf21_1_Acting.md => 03_paf21_1_Acting.md} (100%) create mode 100644 doc/03_research/01_acting/04_research_Acting_Pylot_and_PAF21_2.md rename doc/03_research/01_acting/{autoware_acting.md => 05_autoware_acting.md} (100%) rename doc/03_research/{research_PAF_23/Research_Pylot-Planning_PAF21-Perception.md => 02_perception/05_Research_PAF21-Perception.md} (52%) create mode 100644 doc/03_research/03_planning/09_Research_Pylot_Planning.md rename doc/08_dev_talks/{ => dev_talks_paf22}/sprint_4.md (100%) rename doc/08_dev_talks/{ => dev_talks_paf22}/sprint_5.md (100%) create mode 100644 doc/08_dev_talks/dev_talks_paf23/sprint_1.md diff --git a/doc/00_assets/research_assetes/messages_paf21_2.png b/doc/00_assets/research_assetes/messages_paf21_2.png new file mode 100644 index 0000000000000000000000000000000000000000..6573bf5e7e0e99ff2822eca884754c9fb7f1ad20 GIT binary patch literal 188877 zcmdRWhgVZw(=X~{r`Q0cswhbBy^DZSrAt?lmJpB{AQTk=6#l28*Ml*{ve_j~W(aQ9kS$()t5_dfgV^P8F9%$(29jdYo=a9m+vU|@Ro^oc10 z!$l4ThI5gZE}R~*FD2-lex30()qTtW9pqX)75;J6G}L5ZsENON`0D(reEIEDYhMNi z?&yC%XX2MOof#NT3ZFgEG!JxGpJfU$U&^ALczM~reifTB`()MA4*c2jQmP*+3-(6NF<7}$vl=>= zm@}VWw#19NB*_c=eLXDJ%{xn7(q)Ao7&>#`1q6aV)4ATwr4;N`d6<(l!yyN;36Q$q zq5cLxL8{A)qQeSPozv0PCMhmq+ulTZUa#Tc8z*-QOB?HrSZU6W6z>g&8hy!FaqME? 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SZBzJKL@J7R70NL8LjDK0SWAll literal 0 HcmV?d00001 diff --git a/doc/03_research/01_acting/paf21_1_Acting.md b/doc/03_research/01_acting/03_paf21_1_Acting.md similarity index 100% rename from doc/03_research/01_acting/paf21_1_Acting.md rename to doc/03_research/01_acting/03_paf21_1_Acting.md diff --git a/doc/03_research/01_acting/04_research_Acting_Pylot_and_PAF21_2.md b/doc/03_research/01_acting/04_research_Acting_Pylot_and_PAF21_2.md new file mode 100644 index 00000000..298d8807 --- /dev/null +++ b/doc/03_research/01_acting/04_research_Acting_Pylot_and_PAF21_2.md @@ -0,0 +1,313 @@ +# PAF Research: Robert Fischer + +# PAF22: + +## Acting + +- Longitudinal control + - PID controller +- Lateral control + - Pure Pursuit controller + + ![Untitled](../../00_assets/research_assetes/pure_pursuit.png) + + - Stanley controller + + ![Untitled](../../00_assets/research_assetes/stanley_controller.png) + + +### [List of Inputs/Outputs](https://github.com/una-auxme/paf23/blob/main/doc/03_research/01_acting/02_acting_implementation.md#list-of-inputsoutputs) + +- Subscribes to: + - [nav_msgs/Odometry Message](http://docs.ros.org/en/noetic/api/nav_msgs/html/msg/Odometry.html) : to get the current position and heading + - [nav_msgs/Path Message](https://docs.ros.org/en/api/nav_msgs/html/msg/Path.html) : to get the current trajectory + - emergency breaking msg : to initiate emergency breaking + - speed limit msg : to get the maximum velocity +- Publishes: + - [CarlaEgoVehicleControl.msg](https://carla.readthedocs.io/projects/ros-bridge/en/latest/ros_msgs/#carlaegovehiclecontrolmsg) : to actually control the vehicles throttle, steering + +### [Challenges](https://github.com/una-auxme/paf23/blob/main/doc/03_research/01_acting/02_acting_implementation.md#challenges) + +A short list of challenges for the implementation of a basic acting domain and how they these could be tackled based on the requirements mentioned above. + +- The vehicle needs to know its own position => [nav_msgs/Odometry Message](http://docs.ros.org/en/noetic/api/nav_msgs/html/msg/Odometry.html) or [GNSS](https://carla.readthedocs.io/en/latest/ref_sensors/#gnss-sensor) sensor +- The vehicle needs to know its own velocity => can be calculated from last/current position and time or the [speedometer](https://leaderboard.carla.org/#map-track) pseudosensor can be used +- The vehicle needs to know its planned trajectory => [nav_msgs/Path Message](https://docs.ros.org/en/api/nav_msgs/html/msg/Path.html) this trajectory may need to be updated to accommodate obstacles +- Longitudinal control => a simple PID controller should suffice +- lateral control => Pure Pursuit as well as Stanley controller should be implemented, following tests can show, where to use each controller. +- additional features: + - emergency breaking => this command is supposed to bypass longitudinal and lateral controllers (and should use the bug discoverd by [paf21-2](https://github.com/ll7/paf21-2/tree/main/paf_ros/paf_actor#bugabuses)) + - additional functionality mostly should be added here . + +# PAF21_2 Acting: + +### [Standardroutine](https://github.com/ll7/paf21-2/tree/main/paf_ros/paf_actor#standardroutine) + +![Untitled](../../00_assets/research_assetes/standard_routine_paf21_2.png) + +- Longitudinal control + - PID controller +- Lateral control + - Stanley controller + + → CarlaEgoVehicleControl-Message an Carla + +### [Unstuck-Routine](https://github.com/ll7/paf21-2/tree/main/paf_ros/paf_actor#unstuck-routine) + +Timer und Schwellenwerte um Stuck Situation zu erkennen + +→ paar meter rückwärts ohne lenken + +- **Funktionsweise:** + 1. **Initialisierung:** + - Timer wird auf null gesetzt. + 2. **Überprüfung der Fahrzeugbewegung:** + - Aktuelle Geschwindigkeit wird mit der gewünschten Zielgeschwindigkeit verglichen. + - Falls aktuelle Geschwindigkeit unter einem Schwellenwert liegt und Zielgeschwindigkeit darüber, wird der Timer gestartet. + 3. **Timer-Überwachung:** + - Timer wird verwendet, um die festgefahrene Situation zu behandeln. + - Timer-Wert ist entscheidend und wird durch Schwelle definiert. + 4. **Unstuck-Routine-Auslösung:** + - Wenn Timer einen bestimmten Wert erreicht, wird die Unstuck-Routine aktiviert. + - Actor fährt einige Meter rückwärts, ohne zu lenken. + 5. **Rückkehr zum Normalbetrieb:** + - Nach erfolgreicher Anwendung der Unstuck-Routine kehrt das Fahrzeug zum normalen Betrieb zurück. +- **Notwendige Überlegungen:** + - Schwelle ist entscheidend, um sicherzustellen, dass das Fahrzeug nicht aufgrund minimaler Geschwindigkeitsunterschiede als festgefahren betrachtet wird. + - Timer stellt sicher, dass die Unstuck-Routine nicht sofort ausgelöst wird, sondern nur nach einer vordefinierten Zeit. + +### [Deadlock](https://github.com/ll7/paf21-2/tree/main/paf_ros/paf_actor#deadlock) + +- **Herausforderung:** + - Mögliche Situationen, in denen der Actor aufgrund von Unstimmigkeiten in der Planung und Perception in einer festgefahrenen Lage endet. +- **Ursachen für Deadlocks:** + - Unstimmigkeiten zwischen der Planung der Perception, insbesondere bei Interaktionen mit anderen Verkehrsteilnehmern. + - Unvorhergesehene Ereignisse, die nicht durch Standard- oder Unstuck-Routine gelöst werden können. +- **Perception-Paket:** + - Verantwortlich für sichere Durchquerung durch Sensoren, insbesondere Hinderniserkennung. + - Kann Unstimmigkeiten mit der Planung verursachen. +- **Plannning-Paket:** + - Plant optimale Routen unter Berücksichtigung der besten und schnellsten Wege. + - Kann zu unverhofftem Verhalten führen, wie dem Überqueren der Gegenfahrbahn. +- **Deadlock-Szenarien:** + - Zyklische Wartesituationen, z. B. wenn ein Fahrzeug auf der Gegenfahrbahn wartet und gleichzeitig auf uns wartet. +- **Deadlock-Vermeidungsstrategie:** + - Zustandsmaschine als Lösung, unabhängig von anderen Paketen. + - Laufender Timer überwacht die Dauer, in der sich das Fahrzeug nicht bewegt. + - Überschreitung eines Schwellwerts führt zur Aktivierung der Deadlock-Routine. +- **Deadlock-Routine:** + - Stoppt alle Aktivitäten des Actors. + - Führt schrittweise Manöver durch: Rückwärtsfahren, Warten, Vorwärtsfahren. + - Ziel ist die Befreiung aus festgefahrenen Situationen. +- **Optimierung der Zeitparameter:** + - Kritisch, um unnötige Deadlock-Routine-Auslösungen zu vermeiden. + - Zu kurze Zeiten können zu falschen Deadlock-Erkennungen führen. + - Zu lange Zeiten können wertvolle Zeit bei der Zielerreichung kosten. +- **Zusammenfassung:** + - Die Deadlock-Vermeidungsstrategie basiert auf einer intelligenten Zustandsmaschine und einem Timer, um das Fahrzeug aus komplexen oder simpleren festgefahrenen Situationen zu befreien. + - Die Optimierung der Zeitparameter ist entscheidend für die Wirksamkeit der Deadlock-Vermeidung, um unnötige Unterbrechungen zu verhindern und gleichzeitig effizient zum Ziel zu gelangen. + +### [Verfolgung von Hindernissen](https://github.com/ll7/paf21-2/tree/main/paf_ros/paf_actor#verfolgung-von-hindernissen) + +- **Herausforderungen:** + - Zahlreiche Verkehrsteilnehmer erfordern angepasstes Verhalten für sichere Fahrt. +- **Vorteilhaftes Verhalten:** + - **Bleibe in der Mitte der Spur:** + - Zentrale Positionierung für optimale Sicherheit. + - **Fahre niemandem auf:** + - Vermeide Kollisionen durch sicheres Abstandhalten. + - **Behalte die Fußgänger im Auge:** + - Aufmerksamkeit auf Fußgänger, um Kollisionen zu vermeiden. + - **Passe dich anderen an:** + - Flexibles Verhalten gegenüber anderen Verkehrsteilnehmern. + - **Sei kein Bully:** + - Vermeide aggressives Verhalten gegenüber anderen Fahrzeugen oder Fußgängern. +- **Message-Format (PafObstacleFollowInfo.msg):** + - **speed (float32):** + - Aktuelle Geschwindigkeit des Actors. + - **distance (float32):** + - Entfernung zu einem Hindernis vor dem Fahrzeug. + - **no_target (bool):** + - Signalisiert, ob ein Hindernis vor dem Fahrzeug ist (False) oder ob das Ziel verschwunden ist (True). + - **is_vehicle (bool):** + - Kennzeichnet, ob das Hindernis ein Fahrzeug ist. +- **Umsetzung des Verhaltens:** + - **Hindernisvorhanden (no_target=False):** + - Geschwindigkeit anpassen und Pfad weiterverfolgen. + - **Ziel verschwunden (no_target=True):** + - Rückkehr zum Normalbetrieb. + - **Entfernung zum Hindernis (distance):** + - Ignorieren, wenn zu weit entfernt. + - Abstand halten, wenn gefährlich nahe. + - **Anpassung der Geschwindigkeit (speed):** + - Gleiche Geschwindigkeit wie das Hindernis, um sicher zu folgen. + - Kontrollierte Annäherung, wenn notwendig etwas schneller als das Hindernis. +- **Spezialfall - Fußgänger (is_vehicle=False):** + - Vermeidung von rücksichtslosem Verhalten. + - Physik-bedingte unvorhersehbare Situationen verhindern. + - Kontrollierte Annäherung, um das Ziel erfolgreich zu erreichen. + - Beachtung der Sicherheitsregeln, um Fahrzeugfunktionalität zu erhalten. + +### [Messages](https://github.com/ll7/paf21-2/tree/main/paf_ros/paf_actor#messages) + +![Untitled](../../00_assets/research_assetes/messages_paf21_2.png) + +### [StanleyController](https://github.com/ll7/paf21-2/tree/main/paf_ros/paf_actor#stanleycontroller) + +- **Zuständigkeit:** + - Bestimmung des Lenkeinschlags für autonomes Fahren. +- **Berechnung von Heading Error und Crosstrack Error:** + - Basierend auf dem Paper "[Comparison of lateral controllers for autonomous vehicle: experimental results](https://hal.archives-ouvertes.fr/hal-02459398/document)". + - **Heading Error:** + - Maß für Abweichung der Ausrichtung des Fahrzeugs von der gewünschten Richtung. + - **Crosstrack Error:** + - Maß für seitliche Abweichung des Fahrzeugs von der geplanten Fahrspur. +- **Implementierung:** + - Übernommen von [Gruppe 2](https://github.com/ll7/psaf2/wiki/Path-Tracking-Algorithmen#stanley-methode) aus dem Vorjahr. + - Dokumentation der Implementierung vorhanden. +- **Eignung für Geschwindigkeiten:** + - Sehr gut für niedrige und mittlere Geschwindigkeiten beim Vorwärtsfahren. + - Bei hohen Geschwindigkeiten (>100) neigt das Fahrzeug zum Wobbeln. + - Rückwärtsfahren ist möglich, aber wurde nicht optimal eingebaut. +- **Rückwärtstests:** + - Testinformationen für das Rückwärtsfahren verfügbar, aber nicht von uns benötigt. + - Rückwärtsfahren nicht als Hauptanwendungsfokus. +- **Optimierungspotenzial:** + - Potenzielle Optimierungen könnten erforderlich sein, um Wobbeln bei hohen Geschwindigkeiten zu reduzieren. + - Rückwärtsfahren könnte bei Bedarf weiter optimiert werden. + +### [PID Controller](https://github.com/ll7/paf21-2/tree/main/paf_ros/paf_actor#pid-controller) + +- PID Controller ist dafür zuständig, festzulegen, wie stark Gas gegeben und gebremst wird +- nahezu Gruppe 2 Implementierung + +### [Emergency Modus](https://github.com/ll7/paf21-2/tree/main/paf_ros/paf_actor#emergency-modus) + +- **Zweck:** + - Sofortige Vollbremsung im Notfall. +- **Auslösung:** + - Nachricht von Planning oder Perception an den Actor signalisiert einen Notfall. + - Actor führt eine Vollbremsung durch, um schnell zum Stillstand zu kommen. +- **Ende des Notfalls:** + - Vollbremsung wird gestoppt, wenn eine Nachricht den Notfall als aufgelöst erklärt. +- **Kommunikation zwischen Komponenten:** + - Planning oder Perception sendet Nachricht an den Actor, um den Notfall zu signalisieren. + - Nachfolgende Nachricht informiert darüber, dass der Notfall vorbei ist. +- **Automatische Beendigung des Emergency Modus:** + - Vollbremsung dauert an, bis eine Nachricht den Notfall als aufgelöst erklärt. + +Schnellstes Bremsen durch Testing festgestellt [HIER](https://github.com/ll7/paf21-2/blob/main/docs/paf_actor/backwards/braking.md) + +### Bugabuses + +- Beim Bremsen wird der Rückwärtsgang eingelegt und Gas gegeben. +- Außerdem der Lenker im Falle der Notbremse maximal eingeschlagen, um den Bremsweg zu verringern. Dies führt dazu, dass das Auto nach dem Stillstand weiterhin seitlich abdriftet, weshalb die Notbremse dann wieder gelöst werden muss. + +Tipp: Beim Einparken kann die Notbremse helfen, um seitlich in die Lücke zu rutschen ;) + +# Pylot Acting (Control): + +[pylot.control package — Pylot 0.2 documentation](https://pylot.readthedocs.io/en/latest/pylot.control.html#subpackages) doesnt show any useful documentation + +[Control — Pylot 0.2 documentation](https://pylot.readthedocs.io/en/latest/control.html) same; doesnt show useful documentation + +## Control Types: + +### PID: + +Follows waypoints using a PID controller. + +implements a longitudinal and lateral controller + +### MPC: + +- Utilizes model predictive control for speed and waypoint following. +- Predicts future states using a kinematic model to optimize control inputs. +- Parameters include mpc_horizon, mpc_steps, and mpc_weights + +![Untitled](../../00_assets/research_assetes/mpc.png) + +• cost function can be designed to account for driving comfort + +### Carla_Autopilot: + +- Uses CARLA auto pilot for driving on predefined routes. +- Independent of the planning component, relying on CARLA agent for navigation. +- Useful for testing components like perception or prediction without control concerns. + +## Basic Cotrol Code: + +### **[control_eval_operator.py](https://github.com/erdos-project/pylot/blob/master/pylot/control/control_eval_operator.py)** + +"""Operator that computes the accuracy metrics using reference waypoints +and the achieved waypoints. + +``` +Args: + pose_stream (:py:class:`erdos.ReadStream`): The stream on which the + vehicle transform is received. + waypoints_stream (:py:class:`erdos.ReadStream`): The stream on which + the waypoints are received from the planner. + flags (absl.flags): Object to be used to access absl flags. +""" + +``` + +### **[messages.py](https://github.com/erdos-project/pylot/blob/master/pylot/control/messages.py)** + +"""This class represents a message to be used to send control commands. + +``` +Args: + steer (:obj:`float`): Steer angle between [-1.0, 1.0]. + throttle (:obj:`float`): Throttle command between [0.0, 1.0]. + brake (:obj:`float`): Brake command between [0.0, 1.0]. + hand_brake (bool): Boolean controlling hand-brake engagement. + reverse (bool): Boolean controlling reverse gear engagement. + timestamp (:py:class:`erdos.timestamp.Timestamp`): The timestamp of + the message. +""" + +``` + +### **[pid.py](https://github.com/erdos-project/pylot/blob/master/pylot/control/pid.py)** + +This module implements a longitudinal and lateral controller + +### **[pid_control_operator.py](https://github.com/erdos-project/pylot/blob/master/pylot/control/pid_control_operator.py)** + +Operator that uses PID to follow a list of waypoints. + +``` +The operator waits for the pose and waypoint streams to receive a watermark +message for timestamp t, and then it computes and sends a control command. + +Args: + pose_stream (:py:class:`erdos.ReadStream`): Stream on which pose + info is received. + waypoints_stream (:py:class:`erdos.ReadStream`): Stream on which + :py:class:`~pylot.planning.messages.WaypointMessage` messages are + received. The operator receives waypoints from the planning + operator, and must follow these waypoints. + control_stream (:py:class:`erdos.WriteStream`): Stream on which the + operator sends :py:class:`~pylot.control.messages.ControlMessage` + messages. + flags (absl.flags): Object to be used to access absl flags. + +``` + +### **[utils.py](https://github.com/erdos-project/pylot/blob/master/pylot/control/utils.py)** + +a module that contains some utility functions for the control package, such as converting between different coordinate systems, computing the distance and angle between two points, and clipping the control inputs to the limits1 + +## MPC Control Code: + +The MPC Operator is a component of the Pylot Carla project that uses model predictive control to drive the vehicle. It works by solving an optimization problem that minimizes the **deviation from the desired waypoints** and **speed limit**, while **respecting the physical constraints** of the vehicle. The MPC Operator has the following steps: + +- Receive the waypoints and speed limit from the Planning Operator. The waypoints are a list of coordinates that define the path to follow, and the speed limit is the maximum allowed speed on the road. +- Convert the waypoints from the world coordinate system to the vehicle coordinate system. This makes it easier to compute the error and the control inputs. +- Set up the kinematic model of the vehicle, which describes how the state of the vehicle (position, velocity, heading, etc.) changes with respect to the control inputs (throttle, steering, etc.). +- Define the constraints of the optimization problem, which include the bounds on the control inputs and the state variables, as well as the initial and final conditions. +- Define the cost function of the optimization problem, which is a weighted sum of the errors between the predicted and desired states. The cost function can be tuned by changing the weights of the different terms, such as the cross-track error, the heading error, the speed error, etc. +- Solve the optimization problem using the **`cvxpy`** library, which uses a convex solver to find the optimal control inputs that minimize the cost function. +- Send the control commands to the Simulator Operator or the Car Operator, which apply the throttle, steering, and braking to the vehicle. \ No newline at end of file diff --git a/doc/03_research/01_acting/autoware_acting.md b/doc/03_research/01_acting/05_autoware_acting.md similarity index 100% rename from doc/03_research/01_acting/autoware_acting.md rename to doc/03_research/01_acting/05_autoware_acting.md diff --git a/doc/03_research/01_acting/Readme.md b/doc/03_research/01_acting/Readme.md index ba785f94..aa2614a0 100644 --- a/doc/03_research/01_acting/Readme.md +++ b/doc/03_research/01_acting/Readme.md @@ -2,5 +2,10 @@ This folder contains all the results of our research on acting: +* **PAF22** * [Basics](./01_acting.md) * [Implementation](./02_acting_implementation.md) +* **PAF23** +* [PAF21_1 Acting](./03_paf21_1_Acting.md) +* [PAF21_2 Acting & Pylot Control](./04_research_Acting_Pylot_and_PAF21_2.md) +* [Autoware Control](./05_autoware_acting.md) \ No newline at end of file diff --git a/doc/03_research/research_PAF_23/Research_Pylot-Planning_PAF21-Perception.md b/doc/03_research/02_perception/05_Research_PAF21-Perception.md similarity index 52% rename from doc/03_research/research_PAF_23/Research_Pylot-Planning_PAF21-Perception.md rename to doc/03_research/02_perception/05_Research_PAF21-Perception.md index 33df4320..f036100c 100644 --- a/doc/03_research/research_PAF_23/Research_Pylot-Planning_PAF21-Perception.md +++ b/doc/03_research/02_perception/05_Research_PAF21-Perception.md @@ -1,32 +1,5 @@ # Sprint 0: Research Samuel Kühnel -## Pylot - -## Planning - -- 4 different options -- **Waypoint Planner**: Auto follows predefined waypoints. It recognizes traffic lights and stops at obstacles, but cannot avoid them -- **Freenet-Optimal-Trajecotry-Planner**: CPP code with Python wrapper ([GitHub](https://github.com/erdos-project/frenet_optimal_trajectory_planner)) -→ Predefined line that is used for orientation → Can avoid obstacles! - -![freenet_gif](https://github.com/erdos-project/frenet_optimal_trajectory_planner/raw/master/img/fot2.gif) - -- **RRT\*-Planner**: RRT* algorithm for path planning ([GitHub](https://github.com/erdos-project/rrt_star_planner)) - - Creates random nodes - - Adds nodes to the graph that are not blocked by objects on the road - - Generally terminates as soon as a node is found in the target area - - RRT*: Searches for the shortest path - -![rrt_star_gif](https://github.com/erdos-project/rrt_star_planner/raw/master/img/rrtstar.gif) - -- **Hybrid A\* planner**: Hybrid A* algorithm for path planning ([GitHub](https://github.com/erdos-project/hybrid_astar_planner)) - - Calculates the shortest path between two nodes from a graph - - Similar to Dijkstra's algorithm - - Nodes are estimated based on their costs and promising nodes are selected first - - Hybrid A* algorithm: Not always optimal solution, but in the neighborhood of the optimal solution. - -![hybrid_astar_gif](https://github.com/erdos-project/hybrid_astar_planner/raw/master/img/straight_obstacle.gif) - ## PAF 21-2 ### Perception diff --git a/doc/03_research/02_perception/Readme.md b/doc/03_research/02_perception/Readme.md index 157efa2d..5dca148f 100644 --- a/doc/03_research/02_perception/Readme.md +++ b/doc/03_research/02_perception/Readme.md @@ -6,4 +6,5 @@ This folder contains all the results of research on perception: * [Basics](./02_basics.md) * [First implementation plan](./03_first_implementation_plan.md) * **PAF23** - * [Pylot](./04_pylot.md) + * [Pylot Perception](./04_pylot.md) + * [PAF_21_1 Perception](./05_Research_PAF21-Perception.md) \ No newline at end of file diff --git a/doc/03_research/03_planning/09_Research_Pylot_Planning.md b/doc/03_research/03_planning/09_Research_Pylot_Planning.md new file mode 100644 index 00000000..76aef710 --- /dev/null +++ b/doc/03_research/03_planning/09_Research_Pylot_Planning.md @@ -0,0 +1,28 @@ +# Sprint 0: Research Samuel Kühnel + +## Pylot + +## Planning + +- 4 different options +- **Waypoint Planner**: Auto follows predefined waypoints. It recognizes traffic lights and stops at obstacles, but cannot avoid them +- **Freenet-Optimal-Trajecotry-Planner**: CPP code with Python wrapper ([GitHub](https://github.com/erdos-project/frenet_optimal_trajectory_planner)) +→ Predefined line that is used for orientation → Can avoid obstacles! + +![freenet_gif](https://github.com/erdos-project/frenet_optimal_trajectory_planner/raw/master/img/fot2.gif) + +- **RRT\*-Planner**: RRT* algorithm for path planning ([GitHub](https://github.com/erdos-project/rrt_star_planner)) + - Creates random nodes + - Adds nodes to the graph that are not blocked by objects on the road + - Generally terminates as soon as a node is found in the target area + - RRT*: Searches for the shortest path + +![rrt_star_gif](https://github.com/erdos-project/rrt_star_planner/raw/master/img/rrtstar.gif) + +- **Hybrid A\* planner**: Hybrid A* algorithm for path planning ([GitHub](https://github.com/erdos-project/hybrid_astar_planner)) + - Calculates the shortest path between two nodes from a graph + - Similar to Dijkstra's algorithm + - Nodes are estimated based on their costs and promising nodes are selected first + - Hybrid A* algorithm: Not always optimal solution, but in the neighborhood of the optimal solution. + +![hybrid_astar_gif](https://github.com/erdos-project/hybrid_astar_planner/raw/master/img/straight_obstacle.gif) \ No newline at end of file diff --git a/doc/03_research/03_planning/Readme.md b/doc/03_research/03_planning/Readme.md index aa326cbb..ec451c6f 100644 --- a/doc/03_research/03_planning/Readme.md +++ b/doc/03_research/03_planning/Readme.md @@ -9,3 +9,4 @@ This folder contains all the results of research on planning: * [State machine design](./06_state_machine_design.md) * **PAF23** * [PAF21-1 Planning](./08_paf21-1.md) + * [Pylot Planning](./09_Research_Pylot_Planning.md) diff --git a/doc/08_dev_talks/sprint_4.md b/doc/08_dev_talks/dev_talks_paf22/sprint_4.md similarity index 100% rename from doc/08_dev_talks/sprint_4.md rename to doc/08_dev_talks/dev_talks_paf22/sprint_4.md diff --git a/doc/08_dev_talks/sprint_5.md b/doc/08_dev_talks/dev_talks_paf22/sprint_5.md similarity index 100% rename from doc/08_dev_talks/sprint_5.md rename to doc/08_dev_talks/dev_talks_paf22/sprint_5.md diff --git a/doc/08_dev_talks/dev_talks_paf23/sprint_1.md b/doc/08_dev_talks/dev_talks_paf23/sprint_1.md new file mode 100644 index 00000000..642af4a8 --- /dev/null +++ b/doc/08_dev_talks/dev_talks_paf23/sprint_1.md @@ -0,0 +1,37 @@ +# Sprint 1 + +- [ ] Namen auf Präsentationen packen +- [ ] cleaning up github repo {Robert, Leon} + - [ ] Research issues PR / merge +- [ ] 5- 25 h work for submission fix (Work for 2) {Samuel, Maxi} + - [ ] constructing & updating docker image (archive into docker image) + - [ ] update of branches +- [ ] Analyzation of projects AIM State and IS State (every group) +- [ ] Start working on code +- [ ] detailed understanding of components + + Perception: {Leon, Maxi} + + - [ ] removing panopticsegmentation (if non breaking) + - [ ] what does happen when its removed? + - [ ] (→ replacing it with object detection by Pylot [issue for backlog]) + + Planning: {Julius, Samuel, Alex} + + - [ ] creating visual architecture + - [ ] understanding of components + - [ ] understanding of current Decision Tree + - [ ] does the global routing by the Decision Tree work? + - [ ] lane decisions correct? (holding lane, switching lanes) + - [ ] how well does it perform + - [ ] limitations? + - [ ] (Decision Tree, (vs. ) State Machine [issue for backlog]) + - [ ] comparing to performance of State Machine by Driving Score (if Decision Tree hits its limitations) + - [ ] Decision Tree might be better without needing to test State Machine + - [ ] Composition of local planner + + Acting: {Robert, Alex} + + - [ ] Detailed understanding of components + - [ ] Comparing trajectory with actual actions + - [ ] which new interfaces are needed? (if needed) \ No newline at end of file From 3fd51ba02a0db0fa5b8ef129735a905bb8fe7326 Mon Sep 17 00:00:00 2001 From: Robert Date: Fri, 17 Nov 2023 13:57:26 +0100 Subject: [PATCH 2/4] fixed linter issues --- .../04_research_Acting_Pylot_and_PAF21_2.md | 215 +++++++++--------- doc/03_research/01_acting/Readme.md | 2 +- doc/03_research/02_perception/Readme.md | 2 +- 3 files changed, 105 insertions(+), 114 deletions(-) diff --git a/doc/03_research/01_acting/04_research_Acting_Pylot_and_PAF21_2.md b/doc/03_research/01_acting/04_research_Acting_Pylot_and_PAF21_2.md index 298d8807..871338fe 100644 --- a/doc/03_research/01_acting/04_research_Acting_Pylot_and_PAF21_2.md +++ b/doc/03_research/01_acting/04_research_Acting_Pylot_and_PAF21_2.md @@ -1,30 +1,29 @@ # PAF Research: Robert Fischer -# PAF22: +## PAF22 ## Acting - Longitudinal control - - PID controller + - PID controller - Lateral control - - Pure Pursuit controller - + - Pure Pursuit controller + ![Untitled](../../00_assets/research_assetes/pure_pursuit.png) - + - Stanley controller - + ![Untitled](../../00_assets/research_assetes/stanley_controller.png) - ### [List of Inputs/Outputs](https://github.com/una-auxme/paf23/blob/main/doc/03_research/01_acting/02_acting_implementation.md#list-of-inputsoutputs) - Subscribes to: - - [nav_msgs/Odometry Message](http://docs.ros.org/en/noetic/api/nav_msgs/html/msg/Odometry.html) : to get the current position and heading - - [nav_msgs/Path Message](https://docs.ros.org/en/api/nav_msgs/html/msg/Path.html) : to get the current trajectory - - emergency breaking msg : to initiate emergency breaking - - speed limit msg : to get the maximum velocity + - [nav_msgs/Odometry Message](http://docs.ros.org/en/noetic/api/nav_msgs/html/msg/Odometry.html) : to get the current position and heading + - [nav_msgs/Path Message](https://docs.ros.org/en/api/nav_msgs/html/msg/Path.html) : to get the current trajectory + - emergency breaking msg : to initiate emergency breaking + - speed limit msg : to get the maximum velocity - Publishes: - - [CarlaEgoVehicleControl.msg](https://carla.readthedocs.io/projects/ros-bridge/en/latest/ros_msgs/#carlaegovehiclecontrolmsg) : to actually control the vehicles throttle, steering + - [CarlaEgoVehicleControl.msg](https://carla.readthedocs.io/projects/ros-bridge/en/latest/ros_msgs/#carlaegovehiclecontrolmsg) : to actually control the vehicles throttle, steering ### [Challenges](https://github.com/una-auxme/paf23/blob/main/doc/03_research/01_acting/02_acting_implementation.md#challenges) @@ -36,19 +35,19 @@ A short list of challenges for the implementation of a basic acting domain and h - Longitudinal control => a simple PID controller should suffice - lateral control => Pure Pursuit as well as Stanley controller should be implemented, following tests can show, where to use each controller. - additional features: - - emergency breaking => this command is supposed to bypass longitudinal and lateral controllers (and should use the bug discoverd by [paf21-2](https://github.com/ll7/paf21-2/tree/main/paf_ros/paf_actor#bugabuses)) - - additional functionality mostly should be added here . + - emergency breaking => this command is supposed to bypass longitudinal and lateral controllers (and should use the bug discoverd by [paf21-2](https://github.com/ll7/paf21-2/tree/main/paf_ros/paf_actor#bugabuses)) + - additional functionality mostly should be added here . -# PAF21_2 Acting: +## PAF21_2 Acting ### [Standardroutine](https://github.com/ll7/paf21-2/tree/main/paf_ros/paf_actor#standardroutine) ![Untitled](../../00_assets/research_assetes/standard_routine_paf21_2.png) - Longitudinal control - - PID controller + - PID controller - Lateral control - - Stanley controller + - Stanley controller → CarlaEgoVehicleControl-Message an Carla @@ -56,7 +55,7 @@ A short list of challenges for the implementation of a basic acting domain and h Timer und Schwellenwerte um Stuck Situation zu erkennen -→ paar meter rückwärts ohne lenken +→ paar meter rückwärts ohne lenken - **Funktionsweise:** 1. **Initialisierung:** @@ -73,80 +72,80 @@ Timer und Schwellenwerte um Stuck Situation zu erkennen 5. **Rückkehr zum Normalbetrieb:** - Nach erfolgreicher Anwendung der Unstuck-Routine kehrt das Fahrzeug zum normalen Betrieb zurück. - **Notwendige Überlegungen:** - - Schwelle ist entscheidend, um sicherzustellen, dass das Fahrzeug nicht aufgrund minimaler Geschwindigkeitsunterschiede als festgefahren betrachtet wird. - - Timer stellt sicher, dass die Unstuck-Routine nicht sofort ausgelöst wird, sondern nur nach einer vordefinierten Zeit. + - Schwelle ist entscheidend, um sicherzustellen, dass das Fahrzeug nicht aufgrund minimaler Geschwindigkeitsunterschiede als festgefahren betrachtet wird. + - Timer stellt sicher, dass die Unstuck-Routine nicht sofort ausgelöst wird, sondern nur nach einer vordefinierten Zeit. ### [Deadlock](https://github.com/ll7/paf21-2/tree/main/paf_ros/paf_actor#deadlock) - **Herausforderung:** - - Mögliche Situationen, in denen der Actor aufgrund von Unstimmigkeiten in der Planung und Perception in einer festgefahrenen Lage endet. + - Mögliche Situationen, in denen der Actor aufgrund von Unstimmigkeiten in der Planung und Perception in einer festgefahrenen Lage endet. - **Ursachen für Deadlocks:** - - Unstimmigkeiten zwischen der Planung der Perception, insbesondere bei Interaktionen mit anderen Verkehrsteilnehmern. - - Unvorhergesehene Ereignisse, die nicht durch Standard- oder Unstuck-Routine gelöst werden können. + - Unstimmigkeiten zwischen der Planung der Perception, insbesondere bei Interaktionen mit anderen Verkehrsteilnehmern. + - Unvorhergesehene Ereignisse, die nicht durch Standard- oder Unstuck-Routine gelöst werden können. - **Perception-Paket:** - - Verantwortlich für sichere Durchquerung durch Sensoren, insbesondere Hinderniserkennung. - - Kann Unstimmigkeiten mit der Planung verursachen. + - Verantwortlich für sichere Durchquerung durch Sensoren, insbesondere Hinderniserkennung. + - Kann Unstimmigkeiten mit der Planung verursachen. - **Plannning-Paket:** - - Plant optimale Routen unter Berücksichtigung der besten und schnellsten Wege. - - Kann zu unverhofftem Verhalten führen, wie dem Überqueren der Gegenfahrbahn. + - Plant optimale Routen unter Berücksichtigung der besten und schnellsten Wege. + - Kann zu unverhofftem Verhalten führen, wie dem Überqueren der Gegenfahrbahn. - **Deadlock-Szenarien:** - - Zyklische Wartesituationen, z. B. wenn ein Fahrzeug auf der Gegenfahrbahn wartet und gleichzeitig auf uns wartet. + - Zyklische Wartesituationen, z. B. wenn ein Fahrzeug auf der Gegenfahrbahn wartet und gleichzeitig auf uns wartet. - **Deadlock-Vermeidungsstrategie:** - - Zustandsmaschine als Lösung, unabhängig von anderen Paketen. - - Laufender Timer überwacht die Dauer, in der sich das Fahrzeug nicht bewegt. - - Überschreitung eines Schwellwerts führt zur Aktivierung der Deadlock-Routine. + - Zustandsmaschine als Lösung, unabhängig von anderen Paketen. + - Laufender Timer überwacht die Dauer, in der sich das Fahrzeug nicht bewegt. + - Überschreitung eines Schwellwerts führt zur Aktivierung der Deadlock-Routine. - **Deadlock-Routine:** - - Stoppt alle Aktivitäten des Actors. - - Führt schrittweise Manöver durch: Rückwärtsfahren, Warten, Vorwärtsfahren. - - Ziel ist die Befreiung aus festgefahrenen Situationen. + - Stoppt alle Aktivitäten des Actors. + - Führt schrittweise Manöver durch: Rückwärtsfahren, Warten, Vorwärtsfahren. + - Ziel ist die Befreiung aus festgefahrenen Situationen. - **Optimierung der Zeitparameter:** - - Kritisch, um unnötige Deadlock-Routine-Auslösungen zu vermeiden. - - Zu kurze Zeiten können zu falschen Deadlock-Erkennungen führen. - - Zu lange Zeiten können wertvolle Zeit bei der Zielerreichung kosten. + - Kritisch, um unnötige Deadlock-Routine-Auslösungen zu vermeiden. + - Zu kurze Zeiten können zu falschen Deadlock-Erkennungen führen. + - Zu lange Zeiten können wertvolle Zeit bei der Zielerreichung kosten. - **Zusammenfassung:** - - Die Deadlock-Vermeidungsstrategie basiert auf einer intelligenten Zustandsmaschine und einem Timer, um das Fahrzeug aus komplexen oder simpleren festgefahrenen Situationen zu befreien. - - Die Optimierung der Zeitparameter ist entscheidend für die Wirksamkeit der Deadlock-Vermeidung, um unnötige Unterbrechungen zu verhindern und gleichzeitig effizient zum Ziel zu gelangen. + - Die Deadlock-Vermeidungsstrategie basiert auf einer intelligenten Zustandsmaschine und einem Timer, um das Fahrzeug aus komplexen oder simpleren festgefahrenen Situationen zu befreien. + - Die Optimierung der Zeitparameter ist entscheidend für die Wirksamkeit der Deadlock-Vermeidung, um unnötige Unterbrechungen zu verhindern und gleichzeitig effizient zum Ziel zu gelangen. ### [Verfolgung von Hindernissen](https://github.com/ll7/paf21-2/tree/main/paf_ros/paf_actor#verfolgung-von-hindernissen) - **Herausforderungen:** - - Zahlreiche Verkehrsteilnehmer erfordern angepasstes Verhalten für sichere Fahrt. + - Zahlreiche Verkehrsteilnehmer erfordern angepasstes Verhalten für sichere Fahrt. - **Vorteilhaftes Verhalten:** - - **Bleibe in der Mitte der Spur:** - - Zentrale Positionierung für optimale Sicherheit. - - **Fahre niemandem auf:** - - Vermeide Kollisionen durch sicheres Abstandhalten. - - **Behalte die Fußgänger im Auge:** - - Aufmerksamkeit auf Fußgänger, um Kollisionen zu vermeiden. - - **Passe dich anderen an:** - - Flexibles Verhalten gegenüber anderen Verkehrsteilnehmern. - - **Sei kein Bully:** - - Vermeide aggressives Verhalten gegenüber anderen Fahrzeugen oder Fußgängern. + - **Bleibe in der Mitte der Spur:** + - Zentrale Positionierung für optimale Sicherheit. + - **Fahre niemandem auf:** + - Vermeide Kollisionen durch sicheres Abstandhalten. + - **Behalte die Fußgänger im Auge:** + - Aufmerksamkeit auf Fußgänger, um Kollisionen zu vermeiden. + - **Passe dich anderen an:** + - Flexibles Verhalten gegenüber anderen Verkehrsteilnehmern. + - **Sei kein Bully:** + - Vermeide aggressives Verhalten gegenüber anderen Fahrzeugen oder Fußgängern. - **Message-Format (PafObstacleFollowInfo.msg):** - - **speed (float32):** - - Aktuelle Geschwindigkeit des Actors. - - **distance (float32):** - - Entfernung zu einem Hindernis vor dem Fahrzeug. - - **no_target (bool):** - - Signalisiert, ob ein Hindernis vor dem Fahrzeug ist (False) oder ob das Ziel verschwunden ist (True). - - **is_vehicle (bool):** - - Kennzeichnet, ob das Hindernis ein Fahrzeug ist. + - **speed (float32):** + - Aktuelle Geschwindigkeit des Actors. + - **distance (float32):** + - Entfernung zu einem Hindernis vor dem Fahrzeug. + - **no_target (bool):** + - Signalisiert, ob ein Hindernis vor dem Fahrzeug ist (False) oder ob das Ziel verschwunden ist (True). + - **is_vehicle (bool):** + - Kennzeichnet, ob das Hindernis ein Fahrzeug ist. - **Umsetzung des Verhaltens:** - - **Hindernisvorhanden (no_target=False):** - - Geschwindigkeit anpassen und Pfad weiterverfolgen. - - **Ziel verschwunden (no_target=True):** - - Rückkehr zum Normalbetrieb. - - **Entfernung zum Hindernis (distance):** - - Ignorieren, wenn zu weit entfernt. - - Abstand halten, wenn gefährlich nahe. - - **Anpassung der Geschwindigkeit (speed):** - - Gleiche Geschwindigkeit wie das Hindernis, um sicher zu folgen. - - Kontrollierte Annäherung, wenn notwendig etwas schneller als das Hindernis. + - **Hindernisvorhanden (no_target=False):** + - Geschwindigkeit anpassen und Pfad weiterverfolgen. + - **Ziel verschwunden (no_target=True):** + - Rückkehr zum Normalbetrieb. + - **Entfernung zum Hindernis (distance):** + - Ignorieren, wenn zu weit entfernt. + - Abstand halten, wenn gefährlich nahe. + - **Anpassung der Geschwindigkeit (speed):** + - Gleiche Geschwindigkeit wie das Hindernis, um sicher zu folgen. + - Kontrollierte Annäherung, wenn notwendig etwas schneller als das Hindernis. - **Spezialfall - Fußgänger (is_vehicle=False):** - - Vermeidung von rücksichtslosem Verhalten. - - Physik-bedingte unvorhersehbare Situationen verhindern. - - Kontrollierte Annäherung, um das Ziel erfolgreich zu erreichen. - - Beachtung der Sicherheitsregeln, um Fahrzeugfunktionalität zu erhalten. + - Vermeidung von rücksichtslosem Verhalten. + - Physik-bedingte unvorhersehbare Situationen verhindern. + - Kontrollierte Annäherung, um das Ziel erfolgreich zu erreichen. + - Beachtung der Sicherheitsregeln, um Fahrzeugfunktionalität zu erhalten. ### [Messages](https://github.com/ll7/paf21-2/tree/main/paf_ros/paf_actor#messages) @@ -155,26 +154,26 @@ Timer und Schwellenwerte um Stuck Situation zu erkennen ### [StanleyController](https://github.com/ll7/paf21-2/tree/main/paf_ros/paf_actor#stanleycontroller) - **Zuständigkeit:** - - Bestimmung des Lenkeinschlags für autonomes Fahren. + - Bestimmung des Lenkeinschlags für autonomes Fahren. - **Berechnung von Heading Error und Crosstrack Error:** - - Basierend auf dem Paper "[Comparison of lateral controllers for autonomous vehicle: experimental results](https://hal.archives-ouvertes.fr/hal-02459398/document)". - - **Heading Error:** - - Maß für Abweichung der Ausrichtung des Fahrzeugs von der gewünschten Richtung. - - **Crosstrack Error:** - - Maß für seitliche Abweichung des Fahrzeugs von der geplanten Fahrspur. + - Basierend auf dem Paper "[Comparison of lateral controllers for autonomous vehicle: experimental results](https://hal.archives-ouvertes.fr/hal-02459398/document)". + - **Heading Error:** + - Maß für Abweichung der Ausrichtung des Fahrzeugs von der gewünschten Richtung. + - **Crosstrack Error:** + - Maß für seitliche Abweichung des Fahrzeugs von der geplanten Fahrspur. - **Implementierung:** - - Übernommen von [Gruppe 2](https://github.com/ll7/psaf2/wiki/Path-Tracking-Algorithmen#stanley-methode) aus dem Vorjahr. - - Dokumentation der Implementierung vorhanden. + - Übernommen von [Gruppe 2](https://github.com/ll7/psaf2/wiki/Path-Tracking-Algorithmen#stanley-methode) aus dem Vorjahr. + - Dokumentation der Implementierung vorhanden. - **Eignung für Geschwindigkeiten:** - - Sehr gut für niedrige und mittlere Geschwindigkeiten beim Vorwärtsfahren. - - Bei hohen Geschwindigkeiten (>100) neigt das Fahrzeug zum Wobbeln. - - Rückwärtsfahren ist möglich, aber wurde nicht optimal eingebaut. + - Sehr gut für niedrige und mittlere Geschwindigkeiten beim Vorwärtsfahren. + - Bei hohen Geschwindigkeiten (>100) neigt das Fahrzeug zum Wobbeln. + - Rückwärtsfahren ist möglich, aber wurde nicht optimal eingebaut. - **Rückwärtstests:** - - Testinformationen für das Rückwärtsfahren verfügbar, aber nicht von uns benötigt. - - Rückwärtsfahren nicht als Hauptanwendungsfokus. + - Testinformationen für das Rückwärtsfahren verfügbar, aber nicht von uns benötigt. + - Rückwärtsfahren nicht als Hauptanwendungsfokus. - **Optimierungspotenzial:** - - Potenzielle Optimierungen könnten erforderlich sein, um Wobbeln bei hohen Geschwindigkeiten zu reduzieren. - - Rückwärtsfahren könnte bei Bedarf weiter optimiert werden. + - Potenzielle Optimierungen könnten erforderlich sein, um Wobbeln bei hohen Geschwindigkeiten zu reduzieren. + - Rückwärtsfahren könnte bei Bedarf weiter optimiert werden. ### [PID Controller](https://github.com/ll7/paf21-2/tree/main/paf_ros/paf_actor#pid-controller) @@ -184,17 +183,17 @@ Timer und Schwellenwerte um Stuck Situation zu erkennen ### [Emergency Modus](https://github.com/ll7/paf21-2/tree/main/paf_ros/paf_actor#emergency-modus) - **Zweck:** - - Sofortige Vollbremsung im Notfall. + - Sofortige Vollbremsung im Notfall. - **Auslösung:** - - Nachricht von Planning oder Perception an den Actor signalisiert einen Notfall. - - Actor führt eine Vollbremsung durch, um schnell zum Stillstand zu kommen. + - Nachricht von Planning oder Perception an den Actor signalisiert einen Notfall. + - Actor führt eine Vollbremsung durch, um schnell zum Stillstand zu kommen. - **Ende des Notfalls:** - - Vollbremsung wird gestoppt, wenn eine Nachricht den Notfall als aufgelöst erklärt. + - Vollbremsung wird gestoppt, wenn eine Nachricht den Notfall als aufgelöst erklärt. - **Kommunikation zwischen Komponenten:** - - Planning oder Perception sendet Nachricht an den Actor, um den Notfall zu signalisieren. - - Nachfolgende Nachricht informiert darüber, dass der Notfall vorbei ist. + - Planning oder Perception sendet Nachricht an den Actor, um den Notfall zu signalisieren. + - Nachfolgende Nachricht informiert darüber, dass der Notfall vorbei ist. - **Automatische Beendigung des Emergency Modus:** - - Vollbremsung dauert an, bis eine Nachricht den Notfall als aufgelöst erklärt. + - Vollbremsung dauert an, bis eine Nachricht den Notfall als aufgelöst erklärt. Schnellstes Bremsen durch Testing festgestellt [HIER](https://github.com/ll7/paf21-2/blob/main/docs/paf_actor/backwards/braking.md) @@ -205,21 +204,21 @@ Schnellstes Bremsen durch Testing festgestellt [HIER](https://github.com/ll7/paf Tipp: Beim Einparken kann die Notbremse helfen, um seitlich in die Lücke zu rutschen ;) -# Pylot Acting (Control): +## Pylot Acting (Control) [pylot.control package — Pylot 0.2 documentation](https://pylot.readthedocs.io/en/latest/pylot.control.html#subpackages) doesnt show any useful documentation [Control — Pylot 0.2 documentation](https://pylot.readthedocs.io/en/latest/control.html) same; doesnt show useful documentation -## Control Types: +## Control Types -### PID: +### PID Follows waypoints using a PID controller. implements a longitudinal and lateral controller -### MPC: +### MPC - Utilizes model predictive control for speed and waypoint following. - Predicts future states using a kinematic model to optimize control inputs. @@ -229,20 +228,19 @@ implements a longitudinal and lateral controller • cost function can be designed to account for driving comfort -### Carla_Autopilot: +### Carla_Autopilot - Uses CARLA auto pilot for driving on predefined routes. - Independent of the planning component, relying on CARLA agent for navigation. - Useful for testing components like perception or prediction without control concerns. -## Basic Cotrol Code: +## Basic Cotrol Code ### **[control_eval_operator.py](https://github.com/erdos-project/pylot/blob/master/pylot/control/control_eval_operator.py)** """Operator that computes the accuracy metrics using reference waypoints and the achieved waypoints. -``` Args: pose_stream (:py:class:`erdos.ReadStream`): The stream on which the vehicle transform is received. @@ -251,13 +249,10 @@ Args: flags (absl.flags): Object to be used to access absl flags. """ -``` - ### **[messages.py](https://github.com/erdos-project/pylot/blob/master/pylot/control/messages.py)** """This class represents a message to be used to send control commands. -``` Args: steer (:obj:`float`): Steer angle between [-1.0, 1.0]. throttle (:obj:`float`): Throttle command between [0.0, 1.0]. @@ -268,8 +263,6 @@ Args: the message. """ -``` - ### **[pid.py](https://github.com/erdos-project/pylot/blob/master/pylot/control/pid.py)** This module implements a longitudinal and lateral controller @@ -278,7 +271,6 @@ This module implements a longitudinal and lateral controller Operator that uses PID to follow a list of waypoints. -``` The operator waits for the pose and waypoint streams to receive a watermark message for timestamp t, and then it computes and sends a control command. @@ -294,15 +286,14 @@ Args: messages. flags (absl.flags): Object to be used to access absl flags. -``` - ### **[utils.py](https://github.com/erdos-project/pylot/blob/master/pylot/control/utils.py)** a module that contains some utility functions for the control package, such as converting between different coordinate systems, computing the distance and angle between two points, and clipping the control inputs to the limits1 -## MPC Control Code: +## MPC Control Code -The MPC Operator is a component of the Pylot Carla project that uses model predictive control to drive the vehicle. It works by solving an optimization problem that minimizes the **deviation from the desired waypoints** and **speed limit**, while **respecting the physical constraints** of the vehicle. The MPC Operator has the following steps: +The MPC Operator is a component of the Pylot Carla project that uses model predictive control to drive the vehicle. It works by solving an optimization problem that minimizes the **deviation from the desired waypoints** and **speed limit**, while **respecting the physical constraints** of the vehicle. +The MPC Operator has the following steps: - Receive the waypoints and speed limit from the Planning Operator. The waypoints are a list of coordinates that define the path to follow, and the speed limit is the maximum allowed speed on the road. - Convert the waypoints from the world coordinate system to the vehicle coordinate system. This makes it easier to compute the error and the control inputs. @@ -310,4 +301,4 @@ The MPC Operator is a component of the Pylot Carla project that uses model predi - Define the constraints of the optimization problem, which include the bounds on the control inputs and the state variables, as well as the initial and final conditions. - Define the cost function of the optimization problem, which is a weighted sum of the errors between the predicted and desired states. The cost function can be tuned by changing the weights of the different terms, such as the cross-track error, the heading error, the speed error, etc. - Solve the optimization problem using the **`cvxpy`** library, which uses a convex solver to find the optimal control inputs that minimize the cost function. -- Send the control commands to the Simulator Operator or the Car Operator, which apply the throttle, steering, and braking to the vehicle. \ No newline at end of file +- Send the control commands to the Simulator Operator or the Car Operator, which apply the throttle, steering, and braking to the vehicle. diff --git a/doc/03_research/01_acting/Readme.md b/doc/03_research/01_acting/Readme.md index aa2614a0..4564a30e 100644 --- a/doc/03_research/01_acting/Readme.md +++ b/doc/03_research/01_acting/Readme.md @@ -8,4 +8,4 @@ This folder contains all the results of our research on acting: * **PAF23** * [PAF21_1 Acting](./03_paf21_1_Acting.md) * [PAF21_2 Acting & Pylot Control](./04_research_Acting_Pylot_and_PAF21_2.md) -* [Autoware Control](./05_autoware_acting.md) \ No newline at end of file +* [Autoware Control](./05_autoware_acting.md) diff --git a/doc/03_research/02_perception/Readme.md b/doc/03_research/02_perception/Readme.md index 5dca148f..eef46a2e 100644 --- a/doc/03_research/02_perception/Readme.md +++ b/doc/03_research/02_perception/Readme.md @@ -7,4 +7,4 @@ This folder contains all the results of research on perception: * [First implementation plan](./03_first_implementation_plan.md) * **PAF23** * [Pylot Perception](./04_pylot.md) - * [PAF_21_1 Perception](./05_Research_PAF21-Perception.md) \ No newline at end of file + * [PAF_21_1 Perception](./05_Research_PAF21-Perception.md) From e313c47a66fe4921be30b0653bbb961ba460da07 Mon Sep 17 00:00:00 2001 From: Robert Date: Fri, 17 Nov 2023 13:59:45 +0100 Subject: [PATCH 3/4] fixed mardown linter issues in sprint file --- doc/08_dev_talks/dev_talks_paf23/sprint_1.md | 52 ++++++++++---------- 1 file changed, 26 insertions(+), 26 deletions(-) diff --git a/doc/08_dev_talks/dev_talks_paf23/sprint_1.md b/doc/08_dev_talks/dev_talks_paf23/sprint_1.md index 642af4a8..a0ce04bc 100644 --- a/doc/08_dev_talks/dev_talks_paf23/sprint_1.md +++ b/doc/08_dev_talks/dev_talks_paf23/sprint_1.md @@ -2,36 +2,36 @@ - [ ] Namen auf Präsentationen packen - [ ] cleaning up github repo {Robert, Leon} - - [ ] Research issues PR / merge + - [ ] Research issues PR / merge - [ ] 5- 25 h work for submission fix (Work for 2) {Samuel, Maxi} - - [ ] constructing & updating docker image (archive into docker image) - - [ ] update of branches + - [ ] constructing & updating docker image (archive into docker image) + - [ ] update of branches - [ ] Analyzation of projects AIM State and IS State (every group) - [ ] Start working on code - [ ] detailed understanding of components - + Perception: {Leon, Maxi} - - - [ ] removing panopticsegmentation (if non breaking) - - [ ] what does happen when its removed? - - [ ] (→ replacing it with object detection by Pylot [issue for backlog]) - + + - [ ] removing panopticsegmentation (if non breaking) + - [ ] what does happen when its removed? + - [ ] (→ replacing it with object detection by Pylot [issue for backlog]) + Planning: {Julius, Samuel, Alex} - - - [ ] creating visual architecture - - [ ] understanding of components - - [ ] understanding of current Decision Tree - - [ ] does the global routing by the Decision Tree work? - - [ ] lane decisions correct? (holding lane, switching lanes) - - [ ] how well does it perform - - [ ] limitations? - - [ ] (Decision Tree, (vs. ) State Machine [issue for backlog]) - - [ ] comparing to performance of State Machine by Driving Score (if Decision Tree hits its limitations) - - [ ] Decision Tree might be better without needing to test State Machine - - [ ] Composition of local planner - + + - [ ] creating visual architecture + - [ ] understanding of components + - [ ] understanding of current Decision Tree + - [ ] does the global routing by the Decision Tree work? + - [ ] lane decisions correct? (holding lane, switching lanes) + - [ ] how well does it perform + - [ ] limitations? + - [ ] (Decision Tree, (vs. ) State Machine [issue for backlog]) + - [ ] comparing to performance of State Machine by Driving Score (if Decision Tree hits its limitations) + - [ ] Decision Tree might be better without needing to test State Machine + - [ ] Composition of local planner + Acting: {Robert, Alex} - - - [ ] Detailed understanding of components - - [ ] Comparing trajectory with actual actions - - [ ] which new interfaces are needed? (if needed) \ No newline at end of file + + - [ ] Detailed understanding of components + - [ ] Comparing trajectory with actual actions + - [ ] which new interfaces are needed? (if needed) From c3592fe7fb1c344b7d97e73f9037ca09ddfe4cbd Mon Sep 17 00:00:00 2001 From: Robert Date: Fri, 17 Nov 2023 14:01:55 +0100 Subject: [PATCH 4/4] fixed linter issues in this file --- doc/03_research/03_planning/09_Research_Pylot_Planning.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/doc/03_research/03_planning/09_Research_Pylot_Planning.md b/doc/03_research/03_planning/09_Research_Pylot_Planning.md index 76aef710..e7277d52 100644 --- a/doc/03_research/03_planning/09_Research_Pylot_Planning.md +++ b/doc/03_research/03_planning/09_Research_Pylot_Planning.md @@ -25,4 +25,4 @@ - Nodes are estimated based on their costs and promising nodes are selected first - Hybrid A* algorithm: Not always optimal solution, but in the neighborhood of the optimal solution. -![hybrid_astar_gif](https://github.com/erdos-project/hybrid_astar_planner/raw/master/img/straight_obstacle.gif) \ No newline at end of file +![hybrid_astar_gif](https://github.com/erdos-project/hybrid_astar_planner/raw/master/img/straight_obstacle.gif)