4 papers
A Mixed-Reality Testbed for Autonomous Vehicles
H. M. Sabbir Ahmad, Ehsan Sabouni, Emrullah Celik +4
We propose a mixed-reality, hardware-in-the-loop (HIL) testbed for autonomous vehicles that seamlessly integrates a physical testbed of mobile robots with a high-fidelity simulatio…
Robust and Safe Multi-Agent Reinforcement Learning with Communication for Autonomous Vehicles: From Simulation to Hardware
Keshawn Smith, Zhili Zhang, H M Sabbir Ahmad +5
Deep multi-agent reinforcement learning (MARL) has been demonstrated effectively in simulations for multi-robot problems. For autonomous vehicles, the development of vehicle-to-veh…
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…
Reinforcement Learning-based Receding Horizon Control using Adaptive Control Barrier Functions for Safety-Critical Systems
Ehsan Sabouni, H. M. Sabbir Ahmad, Vittorio Giammarino +3
Optimal control methods provide solutions to safety-critical problems but easily become intractable. Control Barrier Functions (CBFs) have emerged as a popular technique that facil…