Hongpeng Cao

According to our database, Hongpeng Cao authored at least 14 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Physics-model-guided Worst-case Sampling for Safe Reinforcement Learning.

Hongpeng Cao, Yanbing Mao, Lui Sha, Marco Caccamo

CoRR, 2024

Simplex-enabled Safe Continual Learning Machine.

Yihao Cai, Hongpeng Cao, Yanbing Mao, Lui Sha, Marco Caccamo

CoRR, 2024

Equivariant Ensembles and Regularization for Reinforcement Learning in Map-based Path Planning.

Mirco Theile, Hongpeng Cao, Marco Caccamo, Alberto L. Sangiovanni-Vincentelli

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2024

Physics-Regulated Deep Reinforcement Learning: Invariant Embeddings.

Hongpeng Cao, Yanbing Mao, Lui Sha, Marco Caccamo

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

6IMPOSE: bridging the reality gap in 6D pose estimation for robotic grasping.

Hongpeng Cao, Lukas Dirnberger, Daniele Bernardini, Cristina Piazza, Marco Caccamo

Frontiers Robotics AI, October, 2023

Physical Deep Reinforcement Learning: Safety and Unknown Unknowns.

Hongpeng Cao, Yanbing Mao, Lui Sha, Marco Caccamo

CoRR, 2023

Physical Deep Reinforcement Learning Towards Safety Guarantee.

Hongpeng Cao, Yanbing Mao, Lui Sha, Marco Caccamo

CoRR, 2023

Flexible Gear Assembly with Visual Servoing and Force Feedback.

Junjie Ming, Daniel Bargmann, Hongpeng Cao, Marco Caccamo

IROS, 2023

Physics-Model-Regulated Deep Reinforcement Learning Towards Safety & Stability Guarantees.

Hongpeng Cao, Yanbing Mao, Lui Sha, Marco Caccamo

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

Towards Safe AI: Sandboxing DNNs-Based Controllers in Stochastic Games.

Bingzhuo Zhong, Hongpeng Cao, Majid Zamani, Marco Caccamo

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Learning 6D Pose Estimation from Synthetic RGBD Images for Robotic Applications.

Hongpeng Cao, Lukas Dirnberger, Daniele Bernardini, Cristina Piazza, Marco Caccamo

CoRR, 2022

Sandboxing (AI-based) Unverified Controllers in Stochastic Games: An Abstraction-based Approach with Safe-visor Architecture.

Bingzhuo Zhong, Hongpeng Cao, Majid Zamani, Marco Caccamo

CoRR, 2022

Cloud-Edge Training Architecture for Sim-to-Real Deep Reinforcement Learning.

Hongpeng Cao, Mirco Theile, Federico G. Wyrwal, Marco Caccamo

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

2021

Safe-visor Architecture for Sandboxing (AI-based) Unverified Controllers in Stochastic Cyber-Physical Systems.

Bingzhuo Zhong, Abolfazl Lavaei, Hongpeng Cao, Majid Zamani, Marco Caccamo

CoRR, 2021