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Legged robots pose one of the greatest challenges in robotics. Dynamic and agile maneuvers of animals cannot be imitated by existing methods that are crafted by humans. A compelling alternative is reinforcement learning, which requires…

Quadruped robots have shown remarkable mobility on various terrains through reinforcement learning. Yet, in the presence of sparse footholds and risky terrains such as stepping stones and balance beams, which require precise foot placement…

Robotics · Computer Science 2024-08-12 Chong Zhang , Nikita Rudin , David Hoeller , Marco Hutter

We tackle the problem of perceptive locomotion in dynamic environments. In this problem, a quadrupedal robot must exhibit robust and agile walking behaviors in response to environmental clutter and moving obstacles. We present a…

Robotics · Computer Science 2023-02-21 Mingyo Seo , Ryan Gupta , Yifeng Zhu , Alexy Skoutnev , Luis Sentis , Yuke Zhu

Parkour is a grand challenge for legged locomotion that requires robots to overcome various obstacles rapidly in complex environments. Existing methods can generate either diverse but blind locomotion skills or vision-based but specialized…

Quadruped robots demonstrate robust and agile movements in various terrains; however, their navigation autonomy is still insufficient. One of the challenges is that the motion capabilities of the quadruped robot are anisotropic along…

Robotics · Computer Science 2025-12-23 Wentao Zhang , Shaohang Xu , Peiyuan Cai , Lijun Zhu

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…

Quadrupedal robots show great potential for valuable real-world applications such as fire rescue and industrial inspection. Such applications often require urgency and the ability to navigate agilely, which in turn demands the capability to…

Robotics · Computer Science 2026-03-16 Zunzhi You , Haolan Guo , Yunke Wang , Chang Xu

Parkour poses a significant challenge for legged robots, requiring navigation through complex environments with agility and precision based on limited sensory inputs. In this work, we introduce a novel method for training end-to-end visual…

Robotics · Computer Science 2024-09-23 Elliot Chane-Sane , Joseph Amigo , Thomas Flayols , Ludovic Righetti , Nicolas Mansard

Parkour is a grand challenge for legged locomotion, even for quadruped robots, requiring active perception and various maneuvers to overcome multiple challenging obstacles. Existing methods for humanoid locomotion either optimize a…

Robotics · Computer Science 2024-09-27 Ziwen Zhuang , Shenzhe Yao , Hang Zhao

Legged robots have enormous potential in their range of capabilities, from navigating unstructured terrains to high-speed running. However, designing robust controllers for highly agile dynamic motions remains a substantial challenge for…

Robotics · Computer Science 2023-04-20 Laura Smith , J. Chase Kew , Tianyu Li , Linda Luu , Xue Bin Peng , Sehoon Ha , Jie Tan , Sergey Levine

Autonomous robots must navigate reliably in unknown environments even under compromised exteroceptive perception, or perception failures. Such failures often occur when harsh environments lead to degraded sensing, or when the perception…

Robotics · Computer Science 2023-10-06 Jin Jin , Chong Zhang , Jonas Frey , Nikita Rudin , Matias Mattamala , Cesar Cadena , Marco Hutter

We show dynamic locomotion strategies for wheeled quadrupedal robots, which combine the advantages of both walking and driving. The developed optimization framework tightly integrates the additional degrees of freedom introduced by the…

Parkour tasks for quadrupeds have emerged as a promising benchmark for agile locomotion. While human athletes can effectively perceive environmental characteristics to select appropriate footholds for obstacle traversal, endowing legged…

Robotics · Computer Science 2026-01-23 Liang Wang , Kanzhong Yao , Yang Liu , Weikai Qin , Jun Wu , Zhe Sun , Qiuguo Zhu

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…

Developing agile behaviors for legged robots remains a challenging problem. While deep reinforcement learning is a promising approach, learning truly agile behaviors typically requires tedious reward shaping and careful curriculum design.…

Robotics · Computer Science 2020-11-12 Atil Iscen , George Yu , Alejandro Escontrela , Deepali Jain , Jie Tan , Ken Caluwaerts

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…

Robotics · Computer Science 2023-09-26 Xuxin Cheng , Kexin Shi , Ananye Agarwal , Deepak Pathak

Pedipulation leverages the feet of legged robots for mobile manipulation, eliminating the need for dedicated robotic arms. While previous works have showcased blind and task-specific pedipulation skills, they fail to account for static and…

Robotics · Computer Science 2024-11-05 Jonas Stolle , Philip Arm , Mayank Mittal , Marco Hutter

Quadrupedal robots are skillful at locomotion tasks while lacking manipulation skills, not to mention dexterous manipulation abilities. Inspired by the animal behavior and the duality between multi-legged locomotion and multi-fingered…

In this work, we aim to enable legged robots to learn how to interpret human social cues and produce appropriate behaviors through physical human guidance. However, learning through physical engagement can place a heavy burden on users when…

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