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Ruyi Zhou

9 accepted papers

2026

PegasusFlow: Parallel Rolling-Denoising Score Sampling for Robot Diffusion Planner Flow Matching

ICRA 2026poster

Diffusion models offer powerful generative capabilities for robot trajectory planning, yet their practical deployment on robots is hindered by a critical bottleneck: reliance on imitation learning from expert demonstrations. This paradigm is often impractical for specialized robots where data is sca…

2026

Three Percent is Enough: Semi-Supervised Martian Segmentation Labeling With Active Learning

RA-L 2026

Accurate, large-scale Martian segmentation datasets are a cornerstone of autonomous scene understanding in support of exploration and navigation in Martian environments. However, high-quality segmentation labeling on planetary images requires annotators to have professional extraterrestrial geologic

Cited by 0SourceScholar
2025

VLM-Empowered Multi-Mode System for Efficient and Safe Planetary Navigation

IROS 2025

The increasingly complex and diverse planetary exploration environment requires more adaptable and flexible rover navigation strategy. In this study, we propose a VLM-empowered multi-mode system to achieve efficient while safe autonomous navigation for planetary rovers. Vision-Language Model (VLM) i

Cited by 2SourcecodeScholar
2025

Whole-Body Constrained Learning for Legged Locomotion via Hierarchical Optimization

RA-L 2025

Reinforcement learning (RL) has demonstrated impressive performance in legged locomotion over various challenging environments. However, due to the sim-to-real gap and lack of explainability, unconstrained RL policies deployed in the real world still suffer from inevitable safety issues, such as joi

Cited by 2SourceScholar
2024

Identifying Terrain Physical Parameters From Vision - Towards Physical-Parameter-Aware Locomotion and Navigation

RA-L 2024

Identifying the physical properties of the surrounding environment is essential for robotic locomotion and navigation to deal with non-geometric hazards, such as slippery and deformable terrains. It would be of great benefit for robots to anticipate these extreme physical properties before contact;

Cited by 29SourceScholar
2023

Learning-Based End-to-End Navigation for Planetary Rovers Considering Non-Geometric Hazards

RA-L 2023

Autonomous navigation plays an increasingly crucial role in rover-based planetary missions. End-to-end navigation approaches developed upon deep reinforcement learning have enabled great adaptability in complex environments. However, most existing works focus on geometric obstacle avoidance thus hav

Cited by 12SourceScholar
2022

Contact Sequence Planning for Hexapod Robots in Sparse Foothold Environment Based on Monte-Carlo Tree

RA-L 2022

Legged robots can pass through complex field environments by selecting gaits and discrete footholds carefully. Conventional methods plan gaits and footholds separately and treat them as a single-step optimal process. However, such approaches cause poor passability in sparse foothold environments. Th

Cited by 22SourceScholar
2022

Pressing and Rubbing: Physics-Informed Features Facilitate Haptic Terrain Classification for Legged Robots

RA-L 2022

Non-geometric hazards like sinkage and slipping, correlated to terrain categories, have an apparent effect on the locomotion of legged robots. Tactile-based terrain classification is a more accurate way to distinguish terrains in different properties than the vision, but selecting representative fea

Cited by 25SourceScholar
2019

Mapping for Planetary Rovers from Terramechanics Perspective

IROS 2019poster

In an autonomous scientific exploration system, the terrain map generated from mapping process integrates sensing information from multiple aspects and lays the base for decision making processes. With the increasing challenges in planetary exploration, equipping planetary rovers with the principles…

Cited by 13SourceScholar