Zobrazeno 1 - 10
of 364
pro vyhledávání: '"Garg, Kunal"'
Multi-agent robotic systems are prone to deadlocks in an obstacle environment where the system can get stuck away from its desired location under a smooth low-level control policy. Without an external intervention, often in terms of a high-level comm
Externí odkaz:
http://arxiv.org/abs/2404.06413
Distributed, scalable, and safe control of large-scale multi-agent systems (MAS) is a challenging problem. In this paper, we design a distributed framework for safe multi-agent control in large-scale environments with obstacles, where a large number
Externí odkaz:
http://arxiv.org/abs/2401.14554
Autor:
Garg, Kunal, Usevitch, James, Breeden, Joseph, Black, Mitchell, Agrawal, Devansh, Parwana, Hardik, Panagou, Dimitra
This tutorial paper presents recent work of the authors that extends the theory of Control Barrier Functions (CBFs) to address practical challenges in the synthesis of safe controllers for autonomous systems and robots. We present novel CBFs and meth
Externí odkaz:
http://arxiv.org/abs/2312.16719
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 start by reviewing various notions of safety and liveness properties, an
Externí odkaz:
http://arxiv.org/abs/2311.13714
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 agents are required to maintain safety using only local information and re
Externí odkaz:
http://arxiv.org/abs/2311.13014
Autor:
Garg, Kunal, Fan, Chuchu
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 essential. Neural networks can be used for verification of actuator perf
Externí odkaz:
http://arxiv.org/abs/2309.09108
The design of safe-critical control algorithms for systems under Denial-of-Service (DoS) attacks on the system output is studied in this work. We aim to address scenarios where attack-mitigation approaches are not feasible, and the system needs to ma
Externí odkaz:
http://arxiv.org/abs/2303.11640
Autor:
Garg, Kunal, Baranwal, Mayank
This study develops a fixed-time convergent saddle point dynamical system for solving min-max problems under a relaxation of standard convexity-concavity assumption. In particular, it is shown that by leveraging the dynamical systems viewpoint of an
Externí odkaz:
http://arxiv.org/abs/2207.12845
This paper studies provable security guarantees for cyber-physical systems (CPS) under actuator attacks. In particular, we consider CPS safety and propose a new attack-detection mechanism based on a zeroing control barrier function (ZCBF) condition.
Externí odkaz:
http://arxiv.org/abs/2204.03077
Accelerated gradient methods are the cornerstones of large-scale, data-driven optimization problems that arise naturally in machine learning and other fields concerning data analysis. We introduce a gradient-based optimization framework for achieving
Externí odkaz:
http://arxiv.org/abs/2112.01363