7 papers
Model-Based Online Decision Making via Generative Trajectory Planning
Haldun Balim, Yilun Du, Na Li
Online decision-making faces a tension between efficient inference and long-horizon reasoning. Value-based methods rely on short-horizon bootstrapping that limits the propagation o…
RLE-Bench: A Qualifying Exam for Coding Agents as Robot Learning Engineers
Haitong Ma, Chenxiao Gao, Rushi Qiang +2
Coding agents are beginning to move beyond purely digital tasks to tackle physical-world challenges, particularly in robotics. Existing robotics benchmarks, however, primarily focu…
Learning Physical Interaction: A Survey of Tactile- and Force-aware Robot Learning
Shilin Shan, Chuhao Zhou, Ruize Wang +30
Physically grounded robot intelligence requires robots to perceive, reason about, and regulate their interactions with the physical world. This capability is particularly critical…
A Single Diffusion-Policy Controller for Multi-Task Block Pushing with Zero-Shot Sim-to-Real Transfer
Haitong Ma, Haldun Balim, Yang Hu +2
Diffusion policies have shown promising empirical performance in representing and learning complex maneuvers for robots using behavior cloning (BC). In this paper, we explore train…
Learning to Adapt: Representation-Based Reinforcement Learning for Multi-Task Skill Transfer
Aryan Naveen, Haitong Ma, Haldun Balim +1
Reinforcement learning has achieved remarkable success in learning complex control policies, yet its applicability remains limited due to sample inefficiency and poor generalizatio…
Autonomous Robotic Ultrasound System for Liver Follow-up Diagnosis: Pilot Phantom Study
Tianpeng Zhang, Sekeun Kim, Jerome Charton +4
The paper introduces a novel autonomous robot ultrasound (US) system targeting liver follow-up scans for outpatients in local communities. Given a computed tomography (CT) image wi…
Efficient Duple Perturbation Robustness in Low-rank MDPs
Yang Hu, Haitong Ma, Bo Dai +1
The pursuit of robustness has recently been a popular topic in reinforcement learning (RL) research, yet the existing methods generally suffer from efficiency issues that obstruct…