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This paper presents a novel methodology to model and optimize trajectories of a quadrupedal robot with spinal compliance to improve standing jump performance compared to quadrupeds with a rigid spine. We introduce an elastic model for a…

Robotics · Computer Science 2021-09-02 Keran Ye , Konstantinos Karydis

This paper presents three feedback controllers that achieve an asymptotically stable, periodic, and fast walking gait for a 3D (spatial) bipedal robot consisting of a torso, two legs, and passive (unactuated) point feet. The contact between…

Robotics · Computer Science 2010-02-18 Christine Chevallereau , Jessy W. Grizzle , Ching-Long Shih

We present an open-source untethered quadrupedal soft robot platform for dynamic locomotion (e.g., high-speed running and backflipping). The robot is mostly soft (80 vol.%) while driven by four geared servo motors. The robot's soft body and…

Robotics · Computer Science 2025-03-17 Boxi Xia , Jiaming Fu , Hongbo Zhu , Zhicheng Song , Yibo Jiang , Hod Lipson

Previous studies have successfully demonstrated agile and robust locomotion in challenging terrains for quadrupedal robots. However, the bipedal locomotion mode for quadruped robots remains unverified. This paper explores the adaptation of…

A vast number of applications for legged robots entail tasks in complex, dynamic environments. But these environments put legged robots at high risk for limb damage. This paper presents an empirical study of fault tolerant dynamic gaits…

Robotics · Computer Science 2023-09-25 Abriana Stewart-Height , Daniel E. Koditschek

Developing robust locomotion controllers for bipedal robots with closed kinematic chains presents unique challenges, particularly since most reinforcement learning (RL) approaches simplify these parallel mechanisms into serial models during…

Accurate control of a humanoid robot's global position (i.e., its three-dimensional position in the world) is critical to the reliable execution of high-risk tasks such as avoiding collision with pedestrians in a crowded environment. This…

Robotics · Computer Science 2023-04-28 Yuan Gao , Kentaro Barhydt , Christopher Niezrecki , Yan Gu

This article presents Platform Adaptive Locomotion (PAL), a unified control method for quadrupedal robots with different morphologies and dynamics. We leverage deep reinforcement learning to train a single locomotion policy on procedurally…

Robotics · Computer Science 2025-07-11 David Rytz , Suyoung Choi , Wanming Yu , Wolfgang Merkt , Jemin Hwangbo , Ioannis Havoutis

Dynamical System (DS)-based closed-loop control is a simple and effective way to generate reactive motion policies that well generalize to the robotic workspace, while retaining stability guarantees. Lately the formalism has been expanded…

Robotics · Computer Science 2024-06-04 Bernardo Fichera , Aude Billard

Taking inspiration from the natural gait transition mechanism of quadrupeds, devising a good gait transition strategy is important for quadruped robots to achieve energy-efficient locomotion on various terrains and velocities. While…

Robotics · Computer Science 2024-10-15 Daoxun Zhang , Xieyuanli Chen , Zhengyu Zhong , Ming Xu , Zhiqiang Zheng , Huimin Lu

Reinforcement Learning (RL) has seen many recent successes for quadruped robot control. The imitation of reference motions provides a simple and powerful prior for guiding solutions towards desired solutions without the need for meticulous…

Robotics · Computer Science 2023-03-27 Yuni Fuchioka , Zhaoming Xie , Michiel van de Panne

Practical bipedal robot locomotion needs to be both energy efficient and robust to variability and uncertainty. In this paper, we build upon recent works in trajectory optimization for robot locomotion with two primary goals. First, we wish…

Robotics · Computer Science 2018-07-27 Nihar Talele , Katie Byl

This paper presents a novel approach that combines the advantages of both model-based and learning-based frameworks to achieve robust locomotion. The residual modules are integrated with each corresponding part of the model-based framework,…

Robotics · Computer Science 2025-07-25 Min-Gyu Kim , Dongyun Kang , Hajun Kim , Hae-Won Park

Humans and animals are believed to use a very minimal set of trajectories to perform a wide variety of tasks including walking. Our main objective in this paper is two fold 1) Obtain an effective tool to realize these basic motion patterns…

Bipedal locomotion is a key challenge in robotics, particularly for robots like Bolt, which have a point-foot design. This study explores the control of such underactuated robots using constrained reinforcement learning, addressing their…

Legged robots are becoming increasingly agile in exhibiting dynamic behaviors such as running and jumping. Usually, such behaviors are either optimized and engineered offline (i.e. the behavior is designed for before it is needed), either…

Robotics · Computer Science 2024-03-12 Guillaume Bellegarda , Milad Shafiee , Merih Ekin Özberk , Auke Ijspeert

In this paper, with a view toward fast deployment of locomotion gaits in low-cost hardware, we use a linear policy for realizing end-foot trajectories in the quadruped robot, Stoch $2$. In particular, the parameters of the end-foot…

Nowadays, design and development of legged quadruped robots is a quite active area of scientific research. In fact, the legged robots have become popular due to their capabilities to adapt to harsh terrains and diverse environmental…

Various pipes are extensively used in both industrial settings and daily life, but the pipe inspection especially those with narrow sizes are still very challenging with tremendous time and manufacturing consumed. Quadrupedal robots,…

Robotics · Computer Science 2024-12-19 Jing Guo , Ziwei Wang , Weibang Bai

Humanoid locomotion has advanced rapidly with deep reinforcement learning (DRL), enabling robust feet-based traversal over uneven terrain. Yet platforms beyond leg length remain largely out of reach because current RL training paradigms…

Robotics · Computer Science 2026-03-09 Yikai Wang , Tingxuan Leng , Changyi Lin , Shiqi Liu , Shir Simon , Bingqing Chen , Jonathan Francis , Ding Zhao
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