This paper proposes a compact, explicit interface for humanoid robots that enables diverse manipulation skills and demonstrates its feasibility through natural-language-driven task roll-outs.

Development of a compliant full-body telepresence control stack for miniature humanoids, enabling tele-locomotion and manipulation.

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 presents a robot-agnostic compliant-control framework with standardized interfaces for ROS control ecosystem, enabling reusable infrastructure for various manipulators and diverse compliant…

The paper proposes CTRL-STEER, a closed-loop framework that adaptively adjusts intervention strength to stabilize concept regulation and improve task success in Vision-Language-Action models without r…

The paper introduces DexVerse, a large-scale and modular benchmark for dexterous manipulation with 100 tasks, 3 robot arms, 6 hands, and configurable visual variations.

This paper proposes a sensorless four-channel architecture for teleoperation using inverse dynamics modeling, outperforming conventional methods in human-scale manipulation tasks.

The paper presents CONTACTMIMIC, a learning framework that tracks explicit part-level binary contact commands alongside keypoint trajectories for object interaction tasks.

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.

A single robot platform, Handroid, is introduced that can function as both a dexterous hand and a humanoid robot, with interchangeable control and learning frameworks.

The paper presents ViTacWorld, a framework for scalable contact-rich robot manipulation using a visuo-tactile world model.

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

The paper introduces using frozen, generalist value functions as differentiable surrogates to efficiently optimize and analyze new multi-embodiment robot designs without requiring repeated reinforceme…

This paper presents ABot-C0, a motion-control system for quadruped robots, which includes a scalable multi-source motion-data pipeline, robust policy learning, and a unified deployment stack for real-…

A framework called DexCompose is proposed to reuse pretrained dexterous policies for multi-task manipulation with explicit finger-level action ownership.