In recent years, a large number of manipulator robots have been deployed to replace or
assist humans in many repetitive and dangerous tasks. Yet, these robots have complex …

Recently, there has been growing interest in develo** unmanned aircraft systems (UAS)
with advanced onboard autonomous capabilities. This paper describes the current state of …

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 …

Robot control for tasks such as moving around obstacles or gras** objects has advanced
significantly in the last few decades. However, controlling robots to perform complex tasks is …

We propose a cooperative motion and task planning scheme for multi-agent systems where
the agents have independently assigned local tasks, specified as linear temporal logic …

In recent years, formal methods have been extensively used in the design of autonomous
systems. By employing mathematically rigorous techniques, formal methods can provide …

This article proposes a new highly scalable and asymptotically optimal control synthesis
algorithm from linear temporal logic specifications, called STyLu S* for large-Scale optimal …

This paper addresses the problem of finding robot configurations to grasp assembly parts
during a sequence of collaborative assembly operations. We formulate the search for such …

We present a framework for mobile service robot task planning and execution, based on the
use of probabilistic verification techniques for the generation of optimal policies with …

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 …