1 citations · 2 across the 4 of their papers we have counts for
5 papers
Scenario-Based Compositional Statistical Model Checking for Safety Specifications
Abhinav Pomalapally, Arya Raeesi, Kevin Kai-Chun Chang +2
In safety-critical domains such as autonomous driving, systems must be evaluated across a large number of environment conditions, often represented as composite scenarios built fro…
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…
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…
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…
Passivity Tools for Hybrid Learning Rules in Large Populations
Jair Certorio, Kevin Chang, Nuno C. Martins +2
Recent work has pioneered the use of system-theoretic passivity to study equilibrium stability for the dynamics of noncooperative strategic interactions in large populations of lea…