Integrated Task and Motion Planning

TL;DR

This paper defines a class of task and motion planning problems for robots operating in complex environments, surveys existing algorithms, and characterizes their strategies for integrating discrete task planning with continuous motion planning.

Contribution

It introduces a formal class of TAMP problems and provides a comprehensive survey of algorithms and their integration strategies.

Findings

Characterization of solution strategies for continuous subproblems

Analysis of integration techniques for discrete and continuous components

Identification of challenges in solving TAMP problems

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 paper, 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.