Papers for

remote inspection teams

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

Humanoid robot adapts whole-body motions to different terrains in teleoperation

NEXUS: Perceptive Whole-Body Control for Terrain-Adaptive Teleoperation

Abstract: Whole-body teleoperation requires a humanoid robot to reproduce a human operator's behavior even when their terrains differ. This demands that the robot perceive local terrain and adapt its posture and contacts accordingly, rather than copy the operator's motion frame by frame. However, paired motion data linking the same behaviors across flat ground and different terrains remain scarce, limiting supervision for learning terrain-adaptive control. To enable whole-body teleoperation across mismatched terrains, we introduce NEXUS, a perceptive whole-body control framework that combines human motion commands with onboard sensory feedback. We first develop a scalable terrain-aware adaptation algorithm that efficiently generates high-quality motion pairs across motions and terrains without per-motion or per-terrain tuning. Using a paired motion corpus totaling nearly 1,000 hours, we train a perceptive whole-body controller through teacher-student learning to reproduce commanded behaviors across terrains. Experiments demonstrate efficient, scalable generation of high-quality motion data and show that NEXUS combines broad behavioral coverage with terrain adaptability and tracking fidelity, outperforming existing whole-body controllers on the evaluated benchmarks. Zero-shot real-world deployment enables real-time whole-body teleoperation on diverse unseen terrains, further validating the generalization of our method. Project website: https://nexus-humanoid.github.io/

Wed 30 SeptRobotics
The gist
Controlling a robot to mimic a person’s movements is tricky when the robot walks on a different kind of ground than the person. The authors developed NEXUS, a system that lets a robot sense the terrain it is on and adjust its whole-body movements accordingly, instead of copying motions exactly. They created a large dataset of paired motions across terrains and trained the robot to follow human commands while adapting to new terrains. This approach works well even in new environments the robot has never seen before.
Open → 2609.39000v1

Whole-body robot control strategies improve teleoperation efficiency and safety

Understanding Whole-Body Robot Teleoperation Strategies Under Diverse Task Objectives and Constraints

Abstract: This work investigates the control strategies of complex whole-body robot teleoperation that coordinate active perception, bimanual manipulation, and navigation. We developed a hybrid control framework, combining the free-form and constrained control, for the whole-body teleoperation of the TIAGo mobile manipulator. We conducted a user study to explore people's control strategies under different task constraints such as limited time and low tolerance of errors. Our results highlight the effective use of coordinated control in improving task efficiency and reducing the risk of reaching individual joint limits. We discuss our results and their implications for designing future whole-body robot teleoperation systems.

Fri 11 SeptRobotics
The gist
Controlling a robot that can move, see, and use both hands at the same time is very complicated. The authors created a new control method that mixes flexible and precise controls for a specific robot called TIAGo. They studied how people use this system, especially when tasks have limits like finishing quickly or avoiding mistakes. Their findings show that coordinating movement, seeing, and manipulation helps people work faster and avoids stressing the robot’s joints. This helps build better ways to operate robots remotely in the future.
Open → 2609.12384v1