Related papers: ExtremControl: Low-Latency Humanoid Teleoperation …
Telerobotic systems must adapt to new environmental conditions and deal with high uncertainty caused by long-time delays. As one of the best alternatives to human-level intelligence, Reinforcement Learning (RL) may offer a solution to cope…
Humanoid robots promise general-purpose assistance, yet real-world humanoid loco-manipulation remains challenging because it requires whole-body stability, end-effector dexterity, and contact-aware interaction under frequent contact…
Achieving robust safety alignment in large language models (LLMs) while preserving their utility remains a fundamental challenge. Existing approaches often struggle to balance comprehensive safety with fine-grained controllability at the…
We present and characterize a modular, open-source system to perform feedback control experiments on configurations of atoms and molecules in arrays of optical tweezers. The system features a modular, cost-effective computer architecture…
Humans can perform parkour by traversing obstacles in a highly dynamic fashion requiring precise eye-muscle coordination and movement. Getting robots to do the same task requires overcoming similar challenges. Classically, this is done by…
Large-scale data has driven breakthroughs in robotics, from language models to vision-language-action models in bimanual manipulation. However, humanoid robotics lacks equally effective data collection frameworks. Existing humanoid…
Humanoid robots are designed to perform diverse loco-manipulation tasks. However, they face challenges due to their high-dimensional and unstable dynamics, as well as the complex contact-rich nature of the tasks. Model-based optimal control…
Modern distributed training relies heavily on communication compression to reduce the communication overhead. In this work, we study algorithms employing a popular class of contractive compressors in order to reduce communication overhead.…
The teleoperation of complex, kinematically redundant robots with loco-manipulation capabilities represents a challenge for human operators, who have to learn how to operate the many degrees of freedom of the robot to accomplish a desired…
Teleoperation plays a crucial role in enabling robot operations in challenging environments, yet existing limitations in effectiveness and accuracy necessitate the development of innovative strategies for improving teleoperated tasks. This…
Manipulating an environment remotely with a robotic teleoperator introduces novel electromechanical (EM) dynamics between the user and environment. While considerable effort has focused on minimizing these dynamics, there is limited…
This study addresses the challenge of low dexterity in teleoperation tasks caused by limited sensory feedback and visual occlusion. We propose a novel approach that integrates haptic feedback into teleoperation using the adaptive triggers…
Motion retargeting from a human demonstration to a robot is an effective way to reduce the professional requirements and workload of robot programming, but faces the challenges resulting from the differences between humans and robots.…
The deployment of humanoid robots in unstructured, human-centric environments requires navigation capabilities that extend beyond simple locomotion to include robust perception, provable safety, and socially aware behavior. Current…
Recently, many humanoid robots have been increasingly deployed in various facilities, including hospitals and assisted living environments, where they are often remotely controlled by human operators. Their kinematic redundancy enhances…
To enable humanoid robots to work robustly in confined environments, multi-contact motion that makes contacts not only at extremities, such as hands and feet, but also at intermediate areas of the limbs, such as knees and elbows, is…
[...] With the TelePhysicalOperation interface, the user can teleoperate the different capabilities of a robot (e.g., single/double arm manipulation, wheel/leg locomotion) by applying virtual forces on selected robot body parts. This…
Humanoids operating in real-world workspaces must frequently execute task-driven, short-range movements to SE(2) target poses. To be practical, these transitions must be fast, robust, and energy efficient. While learning-based locomotion…
Humans intuitively move to sound, but current humanoid robots lack expressive improvisational capabilities, confined to predefined motions or sparse commands. Generating motion from audio and then retargeting it to robots relies on explicit…
Humanoid robots have the potential to help human workers by realizing physically demanding manipulation tasks such as moving large boxes within warehouses. We define such tasks as Dynamic Mobile Manipulation (DMM). This paper presents a…