The paper proposes FT-WBC, a fault-tolerant loco-manipulation framework for legged manipulators using a decoupled policy architecture, a Fault Estimator, and a Posture Adaptation Module for fault-awar…

This paper proposes coupled egocentric control, a body-following teleoperation approach for whole-body robot control, improving efficiency, reducing effort, and increasing ease of use.

The paper introduces the Task Alignment Benchmark (TAB) to evaluate terminal agents' ability to selectively follow relevant environmental instructions while ignoring misleading distractors, revealing…

The paper proposes a simulation-trained variable impedance control framework for wearable exoskeletons that safely and effectively augments human physical capabilities across multiple tasks.

This tutorial-style review focuses on kinematics of inertial measurement units (IMUs) for human motion capture and introduces methods to determine adequate formulations for sensor measurements.

This paper proposes a human-likeness index based on time laws of human movement to evaluate the comfort of robot movements.

Adaptive data selection significantly improves wearable prediction performance, particularly for individuals with poor baseline health metrics, suggesting that selective data sampling should be tailor…

The paper introduces Entropic Projection Alignment (EPA), a unified framework that estimates, explains, and improves model performance under distribution shift by aligning source and target distributi…

A new framework called subject-conditioned residual diffusion generates personalized lower-limb kinematics at unseen walking speeds from a subject's gait sequence at a single seen speed.

The paper introduces FoLoRA, a novel optimization framework that uses a generalized Rayleigh quotient to achieve a superior balance between adapting foundation models to specific tasks and preserving…

The paper proposes a novel framework to visualize and uncover latent, structured motion phases in deep reinforcement learning locomotion policies by augmenting state observations with action and next-…

This paper presents a complete pipeline for artificial nociception in a robotic arm, converting skin pressure into bio-inspired withdrawal motions using a reflex controller.

Researchers built a compliant, tapered, continuum arm inspired by the elephant trunk using 3D printing and tendon-driven actuation, enabling whole-body grasping of various objects.

The paper proposes SWIM, a novel imitation learning method that can synthesize physically-based swimming motions from a single example, demonstrating superior data efficiency and generalization across…

This paper introduces Test-Time-Training Robot Policies (RoboTTT), a robot model and training recipe that scales visuomotor context to 8K timesteps, enabling new capabilities like one-shot imitation a…