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As both legged robots and embedded compute have become more capable, researchers have started to focus on field deployment of these robots. Robust autonomy in unstructured environments requires perception of the world around the robot in…

Robotics · Computer Science 2022-09-22 Hersh Sanghvi

Crawling is a common locomotion mechanism in soft robots and nonskeletal animals. In this work we propose modeling soft-robotic legged locomotion by approximating it with an equivalent articulated robot with elastic joints. For concreteness…

Soft Condensed Matter · Physics 2020-01-22 Benny Gamus , Lior Salem , Amir D. Gat , Yizhar Or

Touch sensing is widely acknowledged to be important for dexterous robotic manipulation, but exploiting tactile sensing for continuous, non-prehensile manipulation is challenging. General purpose control techniques that are able to…

Deep learning combined with high-resolution tactile sensing could lead to highly capable dexterous robots. However, progress is slow because of the specialist equipment and expertise. The DIGIT tactile sensor offers low-cost entry to…

Robotics · Computer Science 2022-07-19 Nathan F. Lepora , Yijiong Lin , Ben Money-Coomes , John Lloyd

This paper introduces a novel six-axis force/torque sensor tailored for compact and lightweight legged robots. Unlike traditional strain gauge-based sensors, the proposed non-contact design employs photocouplers, enhancing resistance to…

Robotics · Computer Science 2025-02-12 Hyun-Bin Kim , Byeong-Il Ham , Keun-Ha Choi , Kyung-Soo Kim

To use robots in more unstructured environments, we have to accommodate for more complexities. Robotic systems need more awareness of the environment to adapt to uncertainty and variability. Although cameras have been predominantly used in…

Robotics · Computer Science 2025-06-23 Viral Rasik Galaiya

We seek to augment human manipulation by enabling humans to control two robotic arms in addition to their natural arms using their feet. Thereby, the hands are free to perform tasks of high dexterity, while the feet-controlled arms perform…

Robotic manipulation requires both rich multimodal perception and effective learning frameworks to handle complex real-world tasks. See-through-skin (STS) sensors, which combine tactile and visual perception, offer promising sensing…

Robotics · Computer Science 2026-02-10 Yuyang Li , Yinghan Chen , Zihang Zhao , Puhao Li , Tengyu Liu , Siyuan Huang , Yixin Zhu

Stable and robust robotic grasping is essential for current and future robot applications. In recent works, the use of large datasets and supervised learning has enhanced speed and precision in antipodal grasping. However, these methods…

Robotics · Computer Science 2025-02-28 Boya Zhang , Iris Andrussow , Andreas Zell , Georg Martius

The potential of large tactile arrays to improve robot perception for safe operation in human-dominated environments and of high-resolution tactile arrays to enable human-level dexterous manipulation is well accepted. However, the increase…

Robotics · Computer Science 2017-05-16 Brayden Hollis , Stacy Patterson , Jeff Trinkle

Human demonstrations collected by wearable devices (e.g., tactile gloves) provide fast and dexterous supervision for policy learning, and are guided by rich, natural tactile feedback. However, a key challenge is how to transfer…

Robotic manipulation in industrial scenarios such as construction commonly faces uncertain observations in which the state of the manipulating object may not be accurately captured due to occlusions and partial observables. For example,…

Robotics · Computer Science 2025-05-23 Xiao Hu , Yang Ye

To achieve highly dynamic jumps of legged robots, it is essential to control the rotational dynamics of the robot. In this paper, we aim to improve the jumping performance by proposing a unified model for planning highly dynamic jumps that…

Robotics · Computer Science 2021-09-13 Ke Wang , Guiyang Xin , Songyan Xin , Michael Mistry , Sethu Vijayakumar , Petar Kormushev

Much of the literature on robotic perception focuses on the visual modality. Vision provides a global observation of a scene, making it broadly useful. However, in the domain of robotic manipulation, vision alone can sometimes prove…

Robotics · Computer Science 2019-03-11 Justin Lin , Roberto Calandra , Sergey Levine

In robotic manipulation, tactile sensors are indispensable, especially when dealing with soft objects, objects of varying dimensions, or those out of the robot's direct line of sight. Traditional tactile sensors often grapple with…

Robotics · Computer Science 2024-05-24 Abraham George , Yibo Chen , Atharva Dikshit , Peter Pak , Amir Barati Farimani

Teaching dexterity to multi-fingered robots has been a longstanding challenge in robotics. Most prominent work in this area focuses on learning controllers or policies that either operate on visual observations or state estimates derived…

Robotics · Computer Science 2023-03-22 Irmak Guzey , Ben Evans , Soumith Chintala , Lerrel Pinto

Increasing the performance of tactile sensing in robots enables versatile, in-hand manipulation. Vision-based tactile sensors have been widely used as rich tactile feedback has been shown to be correlated with increased performance in…

Robotics · Computer Science 2022-03-10 Won Kyung Do , Monroe Kennedy

Animals locomote robustly and agile, albeit significant sensorimotor delays of their nervous system. The sensorimotor control of legged robots is implemented with much higher frequencies-often in the kilohertz range-and sensor and actuator…

In this paper, a method for stabilizing biped robots stepping by a combination of Divergent Component of Motion (DCM) tracking and step adjustment is proposed. In this method, the DCM trajectory is generated, consistent with the predefined…

Legged robots face significant challenges in moving and navigating on deformable and highly yielding terrain such as mud. We present a resistive force model for legged foot-mud interactions. The model captures rheological behaviors such as…

Robotics · Computer Science 2026-04-15 Xunjie Chen , Liuyin Wang , Xinyan Huang , Jerry Shan , Yantao Shen , Jingang Yi