- main implements CACTO with state = [q,v,t] (joint angles, velocities and time). Inputs: system (default:'-'), TO-method (default: 'pyomo'), and seed (default: None)
- CACTO initializes the variables used both in CACTO.
- TO implements the TO problem of the selected system whose end effector has to reach a target state while avoiding an obstacle and ensuring low control effort. The TO problem is modelled in Pyomo and solved with ipopt.
- RL implements the acotr-critic RL problem of the selected system whose end effector has to reach a target state while avoiding an obstacle and ensuring low control effort.
- environment contains the training functions of the selected system (reset, step (both array and tensor version), and get-end-effector-position functions).
- replay_buffer implements a reply buffer where to store and sample transitions. It implements also a prioritized version of the replay buffer using a segment tree structure implemented in segment_tree to efficiently calculate the cumulative probability needed to sample.
- robot_utils implements the dynamics of the selected system with Pinocchio.
- plot contains the plot functions
- system_conf configures the training for the selected system.
- inits contains the functions for the selected system to warm-start TO (ICS, CACTO's rollout, 0s).
- urdf contains system URDF file.
Systems: double integrator (double_integrator) and 3 DOF manipulator (manipulator)