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cs.RO2025
Efficient Continual Adaptation of Pretrained Robotic Policy with Online Meta-Learned Adapters
Ruiqi Zhu, Endong Sun, Guanhe Huang +1
Continual adaptation is essential for general autonomous agents. For example, a household robot pretrained with a repertoire of skills must still adapt to unseen tasks specific to…
cs.RO2024
Cross Domain Policy Transfer with Effect Cycle-Consistency
Ruiqi Zhu, Tianhong Dai, Oya Celiktutan
Training a robotic policy from scratch using deep reinforcement learning methods can be prohibitively expensive due to sample inefficiency. To address this challenge, transferring…
cs.RO2023
Learning to Solve Tasks with Exploring Prior Behaviours
Ruiqi Zhu, Siyuan Li, Tianhong Dai +2
Demonstrations are widely used in Deep Reinforcement Learning (DRL) for facilitating solving tasks with sparse rewards. However, the tasks in real-world scenarios can often have va…