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Pneumatic soft robots present many advantages in manipulation tasks. Notably, their inherent compliance makes them safe and reliable in unstructured and fragile environments. However, full-body shape sensing for pneumatic soft robots is…

Robotics · Computer Science 2023-03-09 Uksang Yoo , Hanwen Zhao , Alvaro Altamirano , Wenzhen Yuan , Chen Feng

The manual design of soft robots and their controllers is notoriously challenging, but it could be augmented---or, in some cases, entirely replaced---by automated design tools. Machine learning algorithms can automatically propose, test,…

Soft robots are powerful tools for manipulating delicate objects, yet their adoption is hindered by two gaps: the lack of integrated tactile sensing and sensor signal distortion caused by actuator deformations. This paper addresses these…

Robotics · Computer Science 2025-12-04 Chengjin Du , Federico Bernabei , Zhengyin Du , Sergio Decherchi , Matteo Lo Preti , Lucia Beccai

Sim-to-real transfer remains a significant challenge in soft robotics due to the unpredictability introduced by common manufacturing processes such as 3D printing and molding. These processes often result in deviations from simulated…

Soft robots have a myriad of potentials because of their intrinsically compliant bodies, enabling safe interactions with humans and adaptability to unpredictable environments. However, most of them have limited actuation speeds, require…

Soft robots are typically approximated as low-dimensional systems, especially when learning-based methods are used. This leads to models that are limited in their capability to predict the large number of deformation modes and interactions…

Robotics · Computer Science 2022-05-10 Thomas George Thuruthel , Fumiya Iida

This work provides a complete framework for the simulation, co-optimization, and sim-to-real transfer of the design and control of soft legged robots. The compliance of soft robots provides a form of "mechanical intelligence" -- the ability…

Robotics · Computer Science 2022-02-10 Charles Schaff , Audrey Sedal , Matthew R. Walter

Differentiable physics simulation provides an avenue to tackle previously intractable challenges through gradient-based optimization, thereby greatly improving the efficiency of solving robotics-related problems. To apply differentiable…

Robotics · Computer Science 2025-04-08 Min Liu , Gang Yang , Siyuan Luo , Lin Shao

Soft robotic manipulators are generally slow despite their great adaptability, resilience, and compliance. This limitation also extends to current soft robotic micromanipulators. Here, we introduce FilMBot, a 3-DOF film-based,…

Robotics · Computer Science 2026-02-06 Jiangkun Yu , Houari Bettahar , Hakan Kandemir , Quan Zhou

Visual robot navigation within large-scale, semi-structured environments deals with various challenges such as computation intensive path planning algorithms or insufficient knowledge about traversable spaces. Moreover, many…

Robotics · Computer Science 2018-03-12 Fabian Blöchliger , Marius Fehr , Marcin Dymczyk , Thomas Schneider , Roland Siegwart

Compared to traditional rigid robotics, soft robotics has attracted increasing attention due to its advantages as compliance, safety, and low cost. As an essential part of soft robotics, the soft robotic gripper also shows its superior…

Robotics · Computer Science 2021-12-30 Xing Wang , Hanwen Kang , Hongyu Zhou , Wesley Au , Chao Chen

Computational design can excite the full potential of soft robotics that has the drawbacks of being highly nonlinear from material, structure, and contact. Up to date, enthusiastic research interests have been demonstrated for individual…

Robotics · Computer Science 2023-11-22 Yue Xie , Xing Wang , Fumiya Iida , David Howard

Magnetic soft robots embedded with hard magnetic particles enable untethered actuation via external magnetic fields, offering remote, rapid, and precise control, which is highly promising for biomedical applications. However, designing such…

Robotics · Computer Science 2025-07-15 Liwei Wang

With the explosive growth of rigid-body simulators, policy learning in simulation has become the de facto standard for most rigid morphologies. In contrast, soft robotic simulation frameworks remain scarce and are seldom adopted by the soft…

Robotics · Computer Science 2025-11-11 Andrew Choi , Dezhong Tong

Soft Robots distinguish themselves from traditional robots by embracing flexible kinematics. Because of their recent emergence, there exist numerous uncharted territories, including novel actuators, manufacturing processes, and advanced…

Robotics · Computer Science 2024-01-23 Jorge Francisco García-Samartín , Adrián Rieker , Antonio Barrientos

Operating robots precisely and at high speeds has been a long-standing goal of robotics research. Balancing these competing demands is key to enabling the seamless collaboration of robots and humans and increasing task performance. However,…

Soft robotics has emerged as the standard solution for grasping deformable objects, and has proven invaluable for mobile robotic exploration in extreme environments. However, despite this growth, there are no widely adopted computational…

Robotics · Computer Science 2024-07-11 Yue Xie , Josh Pinskier , Lois Liow , David Howard , Fumiya Iida

Fluidically actuated soft robots have promising capabilities such as inherent compliance and user safety. The control of soft robots needs to properly handle nonlinear actuation dynamics, motion constraints, workspace limitations, and…

Robotics · Computer Science 2023-01-02 Filippo A. Spinelli , Robert K. Katzschmann

Soft robots, particularly magnetic soft robots, require specialized simulation tools to accurately model their deformation under external magnetic fields. However, existing platforms often lack dedicated support for magnetic materials,…

Soft robots offer an alternative approach to manipulate inside the constrained space while maintaining the safe interaction with the external environment. Due to its adaptable compliance characteristic, external contact force can easily…

Robotics · Computer Science 2019-06-28 Yue Chen , Long Wang , Kevin Galloway , Isuru Godage , Nabil Simaan , Eric Barth
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