CITATION.cff

cff-version: 1.2.0
title: >-
  Multi-contact task and motion planning guided by video
  demonstration.
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Kateryna
    family-names: Zorina
    email: kateryna.zorina@cvut.cz
    affiliation: 'CIIRC, CVUT'
  - given-names: David
    family-names: Kovar
    affiliation: 'CIIRC, CVUT'
  - given-names: Florent
    family-names: Lamiraux
    affiliation: 'LAAS, CNRS'
  - given-names: Nicolas
    family-names: Mansard
    affiliation: 'LAAS, CNRS'
  - given-names: Justin
    family-names: Carpentier
    affiliation: 'INRIA'
  - given-names: Josef
    family-names: Sivic
    affiliation: 'CIIRC, CVUT'
  - given-names: Vladimir
    family-names: Petrik
    email: vladimir.petrik@cvut.cz
    affiliation: 'CIIRC, CVUT'
identifiers:
  - type: url
    value: >-
      https://hal.laas.fr/hal-03945110/file/2022_Kateryna__Video_Guided_Task_and_Motion_Planner.pdf
    description: Conference paper describing the benchmark.
abstract: >-
  This work aims at leveraging instructional video to guide
  the solving of complex multi-contact task-and-motion
  planning tasks in robotics. Towards this goal, we propose
  an extension of the well-established Rapidly-Exploring
  Random Tree (RRT) planner, which simultaneously grows
  multiple trees around grasp and release states extracted
  from the guiding video. Our key novelty lies in combining
  contact states, and 3D object poses extracted from the
  guiding video with a traditional planning algorithm that
  allows us to solve tasks with sequential dependencies, for
  example, if an object needs to be placed at a specific
  location to be grasped later. To demonstrate the benefits
  of the proposed video-guided planning approach, we design
  a new benchmark with three challenging tasks: (i) 3D
  rearrangement of multiple objects between a table and a
  shelf, (ii) multi-contact transfer of an object through a
  tunnel, and (iii) transferring objects using a tray in a
  similar way a waiter transfers dishes. We demonstrate the
  effectiveness of our planning algorithm on several robots,
  including the Franka Emika Panda and the KUKA KMR iiwa.