Integrated Task and Motion Planning

Abstract

The problem of planning for a robot that operates in environments containing a large number of objects, taking actions to move itself through the world as well as to change the state of the objects, is known as task and motion planning (TAMP). TAMP problems contain elements of discrete task planning, discrete–continuous mathematical programming, and continuous motion planning and thus cannot be effectively addressed by any of these fields directly. In this article, we define a class of TAMP problems and survey algorithms for solving them, characterizing the solution methods in terms of their strategies for solving the continuous-space subproblems and their techniques for integrating the discrete and continuous components of the search.

Document Details

Document Type
Pub Defense Publication
Publication Date
May 03, 2021
Source ID
10.1146/annurev-control-091420-084139

Entities

People

  • Beomjoon Kim
  • Caelan Reed Garrett
  • Leslie P. Kaelbling
  • Rachel Holladay
  • Rohan Chitnis
  • Tom Silver
  • Tomas Lozano-PĂ©rez

Organizations

  • Massachusetts Institute of Technology

Tags

Fields of Study

  • Mathematics

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computer Vision.
  • Operations Research

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Space
  • Space - Spacecraft Maneuvers