Integrated Task and Motion Planning
It addresses the challenge of integrated planning for robotics, but is incremental as it focuses on surveying and characterizing existing approaches rather than introducing new solutions.
The paper defines a class of task and motion planning (TAMP) problems for robots operating in object-rich environments and surveys algorithms that integrate discrete task planning with continuous motion planning, characterizing methods based on their strategies for solving subproblems and combining search components.
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.