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cs.RO2026
ScenicRules: An Autonomous Driving Benchmark with Multi-Objective Specifications and Abstract Scenarios
Kevin Kai-Chun Chang, Ekin Beyazit, Alberto Sangiovanni-Vincentelli +2
Developing autonomous driving systems for complex traffic environments requires balancing multiple objectives, such as avoiding collisions, obeying traffic rules, and making effici…
cs.RO2025
Learning to Dock: A Simulation-based Study on Closing the Sim2Real Gap in Autonomous Underwater Docking
Kevin Chang, Rakesh Vivekanandan, Noah Pragin +2
Autonomous Underwater Vehicle (AUV) docking in dynamic and uncertain environments is a critical challenge for underwater robotics. Reinforcement learning is a promising method for…
cs.RO2025
Learning to Swim: Reinforcement Learning for 6-DOF Control of Thruster-driven Autonomous Underwater Vehicles
Levi Cai, Kevin Chang, Yogesh Girdhar
Controlling AUVs can be challenging because of the effect of complex non-linear hydrodynamic forces acting on the robot, which are significant in water and cannot be ignored. The p…