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Chenpeng Yao

4 accepted papers

2026

A&B-LO: Continuous-Time LiDAR Odometry with Adaptive Non-Uniform B-Spline Trajectory Representation

ICRA 2026poster

LiDAR odometry, fused by inertial measurement units (IMU), is an essential task in robotics navigation. Unlike the mainstream methods compensate the motion distortion of LiDAR data by high frequency inertial sensors, this paper deals with the distortion with continuous-time trajectory representation…

Cited by 0Scholar
2026

Dynamics Are Learned, Not Told: Semi-Supervised Discovery of Latent Dynamics Geometries For Zero-Shot Policy Adaptation

ICML 2026poster

Real-world dynamics shifts pose a critical challenge for reinforcement learning, yet prior methods typically rely on encoding explicitly identified physical parameters into a latent context, a rigid parameterization that proves brittle to unmodeled or compound dynamics variations. We instead investi…

Cited by 0SourceScholar
2024

Relaxing the Limitations of the Optimal Reciprocal Collision Avoidance Algorithm for Mobile Robots in Crowds

RA-L 2024

The Optimal Reciprocal Collision Avoidance (ORCA) algorithm is widely used for modeling agents in collision avoidance scenarios. However, suffering from limitations such as the improper reciprocal assumption that each agent is supposed to take half the responsibility for collision avoidance, the per

Cited by 5SourceScholar
2023

RMRL: Robot Navigation in Crowd Environments With Risk Map-Based Deep Reinforcement Learning

RA-L 2023

Achieving safe and effective navigation in crowds is a crucial yet challenging problem. Recent work has mainly encoded the pedestrian-robot state pairs, which cannot fully capture the interactions among humans. Besides, existing work attempts to achieve “hard” collision avoidance, which may leave no

Cited by 20SourceScholar