no code implementations • 11 Sep 2023 • Kai-Chieh Hsu, Haimin Hu, Jaime Fernández Fisac
Recent years have seen significant progress in the realm of robot autonomy, accompanied by the expanding reach of robotic technologies.
1 code implementation • 5 Apr 2023 • Haimin Hu, Kensuke Nakamura, Kai-Chieh Hsu, Naomi Ehrich Leonard, Jaime Fernández Fisac
We present a multi-agent decision-making framework for the emergent coordination of autonomous agents whose intents are initially undecided.
no code implementations • 6 Dec 2022 • Kai-Chieh Hsu, Duy Phuong Nguyen, Jaime Fernández Fisac
The deployment of robots in uncontrolled environments requires them to operate robustly under previously unseen scenarios, like irregular terrain and wind conditions.
no code implementations • 9 May 2022 • An-Jung Huang, Kai-Chieh Hsu, Tian-Sheuan Chang
Deep learning based superresolution achieves high-quality results, but its heavy computational workload, large buffer, and high external memory bandwidth inhibit its usage in mobile devices.
no code implementations • 20 Jan 2022 • Kai-Chieh Hsu, Allen Z. Ren, Duy Phuong Nguyen, Anirudha Majumdar, Jaime F. Fisac
To improve safety, we apply a dual policy setup where a performance policy is trained using the cumulative task reward and a backup (safety) policy is trained by solving the Safety Bellman Equation based on Hamilton-Jacobi (HJ) reachability analysis.
1 code implementation • 23 Dec 2021 • Kai-Chieh Hsu, Vicenç Rubies-Royo, Claire J. Tomlin, Jaime F. Fisac
Recent successes in reinforcement learning methods to approximately solve optimal control problems with performance objectives make their application to certification problems attractive; however, the Lagrange-type objective used in reinforcement learning is not suitable to encode temporal logic requirements.