Autonomous robots facing a diversity of open environments and performing a variety of tasks
and interactions need explicit deliberation in order to fulfill their missions. Deliberation is …

Recent advances in the areas of multimodal machine learning and artificial intelligence (AI)
have led to the development of challenging tasks at the intersection of Computer Vision …

We consider the problem of constructing abstract representations for planning in high-
dimensional, continuous environments. We assume an agent equipped with a collection of …

In this paper we outline an approach to the integration of task planning and motion planning
that has the following key properties: It is aggressively hierarchical; it makes choices and …

We propose a constraint-based approach to address a class of problems encountered in
combined task and motion planning (CTAMP), which we call kinematically constrained …

We present the first platform-independent evaluation method for task and motion planning
(TAMP). Previously point, various problems have been used to test individual planners for …

Integrating task and motion planning is becoming increasingly important due to the
recognition that a growing number of robotics applications in navigation, search-and-rescue …

We consider the problem of constructing a symbolic description of a continuous, low-level
environment for use in planning. We show that symbols that can represent the preconditions …

We introduce a framework that enables an agent to autonomously learn its own symbolic
representation of a low-level, continuous environment. Propositional symbols are formalized …

Solving problems combining task and motion planning requires searching across a symbolic
search space and a geometric search space. Because of the semantic gap between …