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Quadrupedal robots have emerged as a cutting-edge platform for assisting humans, finding applications in tasks related to inspection and exploration in remote areas. Nevertheless, their floating base structure renders them susceptible to…

Robotics · Computer Science 2023-06-23 I Made Aswin Nahrendra , Minho Oh , Byeongho Yu , Hyungtae Lim , Hyun Myung

Tactile sensation is essential for contact-rich manipulation tasks. It provides direct feedback on object geometry, surface properties, and interaction forces, enhancing perception and enabling fine-grained control. An inherent limitation…

Bimanual manipulation with tactile feedback will be key to human-level robot dexterity. However, this topic is less explored than single-arm settings, partly due to the availability of suitable hardware along with the complexity of…

Robotics · Computer Science 2023-07-14 Yijiong Lin , Alex Church , Max Yang , Haoran Li , John Lloyd , Dandan Zhang , Nathan F. Lepora

Fully autonomous mobile robots have a multitude of potential applications, but guaranteeing robust navigation performance remains an open research problem. For many tasks such as repeated infrastructure inspection, item delivery, or…

Robotics · Computer Science 2021-07-30 Dominic Dall'Osto , Tobias Fischer , Michael Milford

In this paper we propose a novel bipedal locomotion controller that uses noisy exteroception to traverse a wide variety of terrains. Building on the cutting-edge advancements in attention based belief encoding for quadrupedal locomotion,…

Robotics · Computer Science 2023-04-17 Bart van Marum , Matthia Sabatelli , Hamidreza Kasaei

Developing natural and diverse locomotion controllers for quadruped robots that can adapt to complex terrains while preserving motion style remains a significant challenge. Existing imitation-based methods face a fundamental optimization…

Robotics · Computer Science 2026-04-21 Zhiquan Wang , Yunyu Liu , Dipam Patel , Ayush Kumar , Aniket Bera , Bedrich Benes

Legged robots must adapt their gait to navigate unpredictable environments, a challenge that animals master with ease. However, most deep reinforcement learning (DRL) approaches to quadruped locomotion rely on a fixed gait, limiting…

Robotics · Computer Science 2025-06-24 Joseph Humphreys , Chengxu Zhou

Modern quadrupeds are skillful in traversing or even sprinting on uneven terrains in a remote uncontrolled environment. However, survival in the wild requires not only maneuverability, but also the ability to handle potential critical…

Robotics · Computer Science 2024-10-28 Dikai Liu , Tianwei Zhang , Jianxiong Yin , Simon See

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

Animals are capable of precise and agile locomotion using vision. Replicating this ability has been a long-standing goal in robotics. The traditional approach has been to decompose this problem into elevation mapping and foothold planning…

Robotics · Computer Science 2022-11-15 Ananye Agarwal , Ashish Kumar , Jitendra Malik , Deepak Pathak

A motion-based control interface promises flexible robot operations in dangerous environments by combining user intuitions with the robot's motor capabilities. However, designing a motion interface for non-humanoid robots, such as…

Robotics · Computer Science 2022-04-29 Sunwoo Kim , Maks Sorokin , Jehee Lee , Sehoon Ha

Legged locomotion enables robotic systems to traverse extremely challenging terrains. In many real-world scenarios, the terrain is not that difficult and these mixed terrain types introduce the need for flexible use of different walking…

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…

Current approaches to humanoid control generally fall into two paradigms: perceptive locomotion, which handles terrain well but is limited to pedal gaits, and general motion tracking, which reproduces complex skills but ignores…

Robotics · Computer Science 2026-01-13 Ziwen Zhuang , Shaoting Zhu , Mengjie Zhao , Hang Zhao

Fast grasping is critical for mobile robots in logistics, manufacturing, and service applications. Existing methods face fundamental challenges in impact stabilization under high-speed motion, real-time whole-body coordination, and…

Robotics · Computer Science 2026-04-15 Heng Tao , Yiming Zhong , Zemin Yang , Yuexin Ma

Planning locomotion trajectories for legged microrobots is challenging because of their complex morphology, high frequency passive dynamics, and discontinuous contact interactions with their environment. Consequently, such research is often…

This article illustrates the application of deep learning to robot touch by considering a basic yet fundamental capability: estimating the relative pose of part of an object in contact with a tactile sensor. We begin by surveying deep…

Robotics · Computer Science 2020-03-31 Nathan F. Lepora , John Lloyd

Little research into tactile feet has been done for walking robots despite the benefits such feedback could give when walking on uneven terrain. This paper describes the development of a simple, robust and inexpensive tactile foot for…

Robotics · Computer Science 2020-08-13 Elizabeth A. Stone , Nathan F. Lepora , David A. W. Barton

Although bipedal locomotion provides the ability to traverse unstructured environments, it requires careful planning and control to safely walk across without falling. This poses an integrated challenge for the robot to perceive, plan, and…

Large language models (LLMs) have demonstrated the potential to perform high-level planning. Yet, it remains a challenge for LLMs to comprehend low-level commands, such as joint angle targets or motor torques. This paper proposes an…

Robotics · Computer Science 2023-09-15 Yujin Tang , Wenhao Yu , Jie Tan , Heiga Zen , Aleksandra Faust , Tatsuya Harada