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The simulation-to-reality (sim-to-real) transfer of large-scale hydraulic robots presents a significant challenge in robotics because of the inherent slow control response and complex fluid dynamics. The complex dynamics result from the…

Robotics · Computer Science 2026-01-19 Minho Lee , Hyeonseok Kim , Jin Tak Kim , Sangshin Park , Jeong Hyun Lee , Jungsan Cho , Jemin Hwangbo

High-performance actuators are crucial to enable mechanical versatility of lower-limb wearable robots, which are required to be lightweight, highly backdrivable, and with high bandwidth. State-of-the-art actuators, e.g., series elastic…

Robot actuators directly affect the performance of robots, and robot drives directly affect the performance of robot actuators. With the development of robotics, robots have put higher requirements on robot drives, such as high stiffness,…

Robotics · Computer Science 2023-01-23 Le Qi , Dapeng Yang , Baoshi Cao , Zhiqi Li , Yikun Gu , Zongwu Xie , Hong Liu

Several recently released humanoid robots, inspired by the mechanical design of Cassie, employ actuator configurations in which the motors are displaced from the joints to reduce leg inertia. While studies accounting for the full kinematic…

Robotics · Computer Science 2025-10-09 Victor Lutz , Ludovic de Matteis , Virgile Batto , Nicolas Mansard

Series Elastic Actuators provide many benefits in force control of robots in unconstrained environments. These benefits include high force fidelity, extremely low impedance, low friction, and good force control bandwidth. Series Elastic…

Robotics · Computer Science 2009-12-22 Arumugom. S , Muthuraman. S , Ponselvan. V

This paper presents design and control innovations of wearable robots that tackle two barriers to widespread adoption of powered exoskeletons, namely restriction of human movement and versatile control of wearable co-robot systems. First,…

Legged robots have achieved impressive feats in dynamic locomotion in challenging unstructured terrain. However, in entertainment applications, the design and control of these robots face additional challenges in appealing to human…

While quadruped robots usually have good stability and load capacity, bipedal robots offer a higher level of flexibility / adaptability to different tasks and environments. A multi-modal legged robot can take the best of both worlds. In…

Robotics · Computer Science 2022-02-25 Chen Yu , Andre Rosendo

Recent advances in deep reinforcement learning (RL) based techniques combined with training in simulation have offered a new approach to developing robust controllers for legged robots. However, the application of such approaches to real…

Robotics · Computer Science 2023-08-08 Rohan Pratap Singh , Zhaoming Xie , Pierre Gergondet , Fumio Kanehiro

Controlled execution of dynamic motions in quadrupedal robots, especially those with articulated soft bodies, presents a unique set of challenges that traditional methods struggle to address efficiently. In this study, we tackle these…

Robotics · Computer Science 2024-03-05 Francecso Vezzi , Jiatao Ding , Antonin Raffin , Jens Kober , Cosimo Della Santina

Wearable and legged robot designers face multiple challenges when choosing actuation. Traditional fully actuated designs using electric motors are multifunctional but oversized and inefficient for bearing conservative loads and for being…

Robotics · Computer Science 2025-11-17 Jeff Denis , Frederic Laberge , Jean-Sebastien Plante , Alexandre Girard

Parallel-elastic joints can improve the efficiency and strength of robots by assisting the actuators with additional torques. For these benefits to be realized, a spring needs to be carefully designed. However, designing robots is an…

Robotics · Computer Science 2023-01-10 Filip Bjelonic , Joonho Lee , Philip Arm , Dhionis Sako , Davide Tateo , Jan Peters , Marco Hutter

Model-free reinforcement learning (RL) for legged locomotion commonly relies on a physics simulator that can accurately predict the behaviors of every degree of freedom of the robot. In contrast, approximate reduced-order models are…

Robotics · Computer Science 2022-02-17 Zhaoming Xie , Xingye Da , Buck Babich , Animesh Garg , Michiel van de Panne

Impressive animal locomotion capabilities are mediated by the co-evolution of the skeletal morphology and muscular properties. Legged robot performance would also likely benefit from the co-optimization of actuators and leg morphology.…

Robotics · Computer Science 2022-02-28 Karthik Urs , Challen Enninful Adu , Elliott J. Rouse , Talia Y. Moore

This study is aimed at addressing the problem of fault tolerance of quadruped robots to actuator failure, which is critical for robots operating in remote or extreme environments. In particular, an adaptive curriculum reinforcement learning…

Robotics · Computer Science 2024-10-28 Wataru Okamoto , Hiroshi Kera , Kazuhiko Kawamoto

This paper presents a robotic system where the gear-ratio of an actuator is dynamically changed to either leverage or attenuate the natural load dynamics. Based on this principle, lightweight robotic systems can be made fast and strong;…

Robotics · Computer Science 2024-05-24 Alexandre Girard , H. Harry Asada

Legged manipulators extend robotic capabilities beyond static manipulation by integrating agile locomotion with versatile arm control. However, achieving precise manipulation while maintaining coordinated locomotion remains a major…

In biomechanics and robotics, elasticity plays a crucial role in enhancing locomotion efficiency and stability. Traditional approaches in legged robots often employ series elastic actuators (SEA) with discrete rigid components, which, while…

Robotics · Computer Science 2024-11-12 Robin Bendfeld , C. David Remy

This paper presents a scalable and adaptive control framework for legged robots that integrates Iterative Learning Control (ILC) with a biologically inspired torque library (TL), analogous to muscle memory. The proposed method addresses key…

Robotics · Computer Science 2026-04-10 Jing Cheng , Yasser G. Alqaham , Zhenyu Gan , Amit K. Sanyal

Designing agile locomotion for quadruped robots often requires extensive expertise and tedious manual tuning. In this paper, we present a system to automate this process by leveraging deep reinforcement learning techniques. Our system can…

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