1 citations · 1 across the 8 of their papers we have counts for
7 papers
Learning More from Less: Reinforcement Learning from Hindsight
Iris Xu, Sunshine Jiang, John Marangola +8
Reinforcement learning (RL) is increasingly used to post-train vision-language-action (VLA) models, but every update consumes robot rollouts that are slow and costly to collect, ma…
Remember what you did?: Learning Behavioral Memories for Partially Observable Object Manipulation
Kuancheng Wang, Seungho Yeom, Jinglin Cao +3
Long horizon, contact-rich manipulation is inherently partially observable. This is as a single visual observation rarely captures a robot's full action context, including prior at…
SteadyTray: Learning Object Balancing Tasks in Humanoid Tray Transport via Residual Reinforcement Learning
Anlun Huang, Zhenyu Wu, Soofiyan Atar +2
Stabilizing unsecured payloads against the inherent oscillations of dynamic bipedal locomotion remains a critical engineering bottleneck for humanoids in unstructured environments.…
SurgIRL: Towards Life-Long Learning for Surgical Automation by Incremental Reinforcement Learning
Yun-Jie Ho, Zih-Yun Chiu, Yuheng Zhi +1
Surgical automation holds immense potential to improve the outcome and accessibility of surgery. Recent studies use reinforcement learning to learn policies that automate different…
KineDepth: Utilizing Robot Kinematics for Online Metric Depth Estimation
Soofiyan Atar, Yuheng Zhi, Florian Richter +1
Depth perception is essential for a robot's spatial and geometric understanding of its environment, with many tasks traditionally relying on hardware-based depth sensors like RGB-D…
Data-driven Actuator Selection for Artificial Muscle-Powered Robots
Taylor West Henderson, Yuheng Zhi, Angela Liu +1
Even though artificial muscles have gained popularity due to their compliant, flexible, and compact properties, there currently does not exist an easy way of making informed decisi…