activity
20232025
most citedGCBF+: A Neural Graph Control Barrier Function Framework for Distributed Safe Multi-Agent Control

41 citations · 45 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2025

Hierarchical Multi-Agent Reinforcement Learning with Control Barrier Functions for Safety-Critical Autonomous Systems

H. M. Sabbir Ahmad, Ehsan Sabouni, Alexander Wasilkoff +6

We address the problem of safe policy learning in multi-agent safety-critical autonomous systems. In such systems, it is necessary for each agent to meet the safety requirements at…

cs.RO2024

Failure Prediction from Limited Hardware Demonstrations

Anjali Parashar, Kunal Garg, Joseph Zhang +1

Prediction of failures in real-world robotic systems either requires accurate model information or extensive testing. Partial knowledge of the system model makes simulation-based f…

cs.RO2024

Foundation Models to the Rescue: Deadlock Resolution in Connected Multi-Robot Systems

Kunal Garg, Songyuan Zhang, Jacob Arkin +1

Connected multi-agent robotic systems (MRS) are prone to deadlocks in an obstacle environment where the robots can get stuck away from their desired locations under a smooth low-le…

cs.RO2024★ 41 cited

GCBF+: A Neural Graph Control Barrier Function Framework for Distributed Safe Multi-Agent Control

Songyuan Zhang, Oswin So, Kunal Garg +1

Distributed, scalable, and safe control of large-scale multi-agent systems is a challenging problem. In this paper, we design a distributed framework for safe multi-agent control i…

cs.RO2023

Learning Safe Control for Multi-Robot Systems: Methods, Verification, and Open Challenges

Kunal Garg, Songyuan Zhang, Oswin So +2

In this survey, we review the recent advances in control design methods for robotic multi-agent systems (MAS), focussing on learning-based methods with safety considerations. We st…

eess.SY2023★ 4 cited

Neural Graph Control Barrier Functions Guided Distributed Collision-avoidance Multi-agent Control

Songyuan Zhang, Kunal Garg, Chuchu Fan

We consider the problem of designing distributed collision-avoidance multi-agent control in large-scale environments with potentially moving obstacles, where a large number of agen…

cs.RO2023

Neural Network-based Fault Detection and Identification for Quadrotors using Dynamic Symmetry

Kunal Garg, Chuchu Fan

Autonomous robotic systems, such as quadrotors, are susceptible to actuator faults, and for the safe operation of such systems, timely detection and isolation of these faults is es…