activity
20102023
most citedEnd-to-End Safe Reinforcement Learning through Barrier Functions for Safety-Critical Continuous Control Tasks

43 citations · 168 across the 35 of their papers we have counts for

collaborators
Showing 2020Show all

5 papers · 1 filter

cs.AI2020★ 6 cited

Constrained Risk-Averse Markov Decision Processes

Mohamadreza Ahmadi, Ugo Rosolia, Michel D. Ingham +2

We consider the problem of designing policies for Markov decision processes (MDPs) with dynamic coherent risk objectives and constraints. We begin by formulating the problem in a L…

cs.RO2020★ 7 cited

Reactive motion planning with probabilistic safety guarantees

Yuxiao Chen, Ugo Rosolia, Chuchu Fan +2

Motion planning in environments with multiple agents is critical to many important autonomous applications such as autonomous vehicles and assistive robots. This paper considers th…

cs.MA2020★ 1 cited

Rules of the Road: Safety and Liveness Guarantees for Autonomous Vehicles

Karena X. Cai, Tung Phan-Minh, Soon-Jo Chung +1

The ability to guarantee safety and progress for all vehicles is vital to the success of the autonomous vehicle industry. We present a framework for designing autonomous vehicle be…

eess.SY2020

Formal Test Synthesis for Safety-Critical Autonomous Systems based on Control Barrier Functions

Prithvi Akella, Mohamadreza Ahmadi, Richard M. Murray +1

The prolific rise in autonomous systems has led to questions regarding their safe instantiation in real-world scenarios. Failures in safety-critical contexts such as human-robot in…

eess.SY2020★ 4 cited

Counter-example Guided Learning of Bounds on Environment Behavior

Yuxiao Chen, Sumanth Dathathri, Tung Phan-Minh +1

There is a growing interest in building autonomous systems that interact with complex environments. The difficulty associated with obtaining an accurate model for such environments…