A typical approach to creating complex robot behaviors is to compose atomic controllers, or
skills, such that the resulting behavior satisfies a high-level task; however, when a task …

This paper presents an incremental replanning algorithm, dubbed LTL-D*, for temporal-logic-
based task planning in a dynamically changing environment. Unexpected changes in the …

Operating under real world conditions is challenging due to the possibility of a wide range of
failures induced by execution errors and state uncertainty. In relatively benign settings, such …

We address the problem of modeling, refining, and repairing formal specifications for robotic
missions using assume-guarantee contracts. We show how to model mission specifications …

This paper presents a framework that enables robots to automatically recover from
assumption violations of high-level specifications during task execution. In contrast to …

Robots hold the promise of becoming an integral part of human life by hel** us in our
homes, out on farms and in our factories. However, current robots lack the motor skills …

A major goal of artificial intelligence (AI) is to create agents capable of acting effectively in a
wide variety of complex environments. A popular framework for modelling decision-making …

This paper presents and gives an overview of the recently emerging field of Neuro-Symbolic
Robotics. With the advances in computational resources, robust neural architectures, and …

A typical approach for producing complex robot behaviors is to compose atomic controllers
(or skills) such that the resulting behavior satisfies a high-level task. However, when a task …

Trajectory learning from demonstrations has the ability to interactively teach robots
newskills, eliminating the need for manual programming of a desired behavior. In this thesis …