Safe-visor Architecture for Sandboxing (AI-based) Unverified Controllers in Stochastic Cyber-Physical Systems. - Bingzhuo Zhong; Abolfazl Lavaei; Hongpeng Cao; Majid Zamani 001; Marco Caccamo (CoRR, 2021)

Cloud-Edge Training Architecture for Sim-to-Real Deep Reinforcement Learning. - Hongpeng Cao; Mirco Theile; Federico G. Wyrwal; Marco Caccamo (IROS, 2022)

Sandboxing (AI-based) Unverified Controllers in Stochastic Games: An Abstraction-based Approach with Safe-visor Architecture. - Bingzhuo Zhong; Hongpeng Cao; Majid Zamani 001; Marco Caccamo (CoRR, 2022)

Learning 6D Pose Estimation from Synthetic RGBD Images for Robotic Applications. - Hongpeng Cao; Lukas Dirnberger; Daniele Bernardini 002; Cristina Piazza; Marco Caccamo (CoRR, 2022)

Towards Safe AI: Sandboxing DNNs-Based Controllers in Stochastic Games. - Bingzhuo Zhong; Hongpeng Cao; Majid Zamani 001; Marco Caccamo (AAAI, 2023)

Physics-Model-Regulated Deep Reinforcement Learning Towards Safety & Stability Guarantees. - Hongpeng Cao; Yanbing Mao; Lui Sha; Marco Caccamo (CDC, 2023)

Flexible Gear Assembly with Visual Servoing and Force Feedback. - Junjie Ming; Daniel Bargmann; Hongpeng Cao; Marco Caccamo (IROS, 2023)

Physical Deep Reinforcement Learning Towards Safety Guarantee. - Hongpeng Cao; Yanbing Mao; Lui Sha; Marco Caccamo (CoRR, 2023)

Physical Deep Reinforcement Learning: Safety and Unknown Unknowns. - Hongpeng Cao; Yanbing Mao; Lui Sha; Marco Caccamo (CoRR, 2023)

6IMPOSE: bridging the reality gap in 6D pose estimation for robotic grasping. - Hongpeng Cao; Lukas Dirnberger; Daniele Bernardini 002; Cristina Piazza; Marco Caccamo (Frontiers Robotics AI, 2023)

Physics-Regulated Deep Reinforcement Learning: Invariant Embeddings. - Hongpeng Cao; Yanbing Mao; Lui Sha; Marco Caccamo (ICLR, 2024)

Equivariant Ensembles and Regularization for Reinforcement Learning in Map-based Path Planning. - Mirco Theile; Hongpeng Cao; Marco Caccamo; Alberto L. Sangiovanni-Vincentelli (IROS, 2024)

Simplex-enabled Safe Continual Learning Machine. - Yihao Cai; Hongpeng Cao; Yanbing Mao; Lui Sha; Marco Caccamo (CoRR, 2024)

Physics-model-guided Worst-case Sampling for Safe Reinforcement Learning. - Hongpeng Cao; Yanbing Mao; Lui Sha; Marco Caccamo (CoRR, 2024)

NLBAC: A neural ODE-based algorithm for state-wise stable and safe reinforcement learning. - Liqun Zhao; Keyan Miao; Hongpeng Cao; Konstantinos Gatsis; Antonis Papachristodoulou (Neurocomputing, 2025)

Runtime Learning of Quadruped Robots in Wild Environments. - Yihao Cai; Yanbing Mao; Lui Sha; Hongpeng Cao; Marco Caccamo (CoRR, 2025)

Bregman Centroid Guided Cross-Entropy Method. - Yuliang Gu; Hongpeng Cao; Marco Caccamo; Naira Hovakimyan (CoRR, 2025)

Observations Meet Actions: Learning Control-Sufficient Representations for Robust Policy Generalization. - Yuliang Gu; Hongpeng Cao; Marco Caccamo; Naira Hovakimyan (CoRR, 2025)