Despite the recent successes in robotics, artificial intelligence and computer vision, a
complete artificial agent necessarily must include active perception. A multitude of ideas and …

This paper provides a framework to automatically generate a hybrid controller that
guarantees that the robot can achieve its task when a robot model, a class of admissible …

We present a model-free reinforcement learning algorithm to synthesize control policies that
maximize the probability of satisfying high-level control objectives given as Linear Temporal …

In this paper, we address the temporal logic motion planning problem for mobile robots that
are modeled by second order dynamics. Temporal logic specifications can capture the usual …

We consider the following problem: given a linear system and a linear temporal logic (LTL)
formula over a set of linear predicates in its state variables, find a feedback control law with …

We propose a representation and a planning algorithm able to deal with problems
integrating task planning as well as motion and manipulation planning knowledge involving …

Given a robot model and a class of admissible environments, this paper provides a
framework for automatically and verifiably composing controllers that satisfy high level task …

We present a computational framework for automatic synthesis of decentralized
communication and control strategies for a robotic team from global specifications, which are …

Recently, Linear Temporal Logic (LTL) has been successfully applied to high-level task and
motion planning problems for mobile robots. One of the main attributes of LTL is its close …

We present a computational framework for automatic synthesis of control and
communication strategies for a robotic team from task specifications that are given as regular …