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Adapting upper-limb impedance (i.e., stiffness, damping, inertia) is essential for humans interacting with dynamic environments for executing grasping or manipulation tasks. On the other hand, control methods designed for state-of-the-art…

Robotics · Computer Science 2022-12-20 Laura Ferrante , Mohan Sridharan , Claudio Zito , Dario Farina

This contribution investigates the connection between Isogeometric Analysis (IgA) and the Partial Element Equivalent Circuit (PEEC) method for electrostatic problems. We demonstrate that using the spline-based geometry concepts from IgA…

Computational Engineering, Finance, and Science · Computer Science 2022-09-30 Riccardo Torchio , Maximilian Nolte , Sebastian Schöps , Albert E. Ruehli

A limiting factor towards the wide routine use of wearables devices for continuous healthcare monitoring is their cumbersome and obtrusive nature. This is particularly true for electroencephalography (EEG) recordings, which require the…

Signal Processing · Electrical Eng. & Systems 2021-05-20 Laura M. Ferrari , Guy Abi Hanna , Paolo Volpe , Esma Ismailova , François Bremond , Maria A. Zuluaga

Reinforcement learning (RL) approaches based on Markov Decision Processes (MDPs) are predominantly applied in the robot joint space, often relying on limited task-specific information and partial awareness of the 3D environment. In…

Robotics · Computer Science 2026-03-09 Bingkun Huang , Yuhe Gong , Zewen Yang , Tianyu Ren , Luis Figueredo

Soft adhesive pads are needed for many robotics applications, and one approach is based on electroadhesion. Here we present a general analytic model and numerical results for electroadhesion for soft solids with arbitrary time-dependent…

Soft Condensed Matter · Physics 2019-08-06 Bo N. J. Persson , Jianglong Guo

Machine learning, artificial intelligence and especially deep learning based approaches are often used to simplify or eliminate the burden of programming industrial robots. Using these approaches robots inherently learn a skill instead of…

Robotics · Computer Science 2021-04-22 Sanaz Behbahani , Siddharth Chhatpar , Said Zahrai , Vishakh Duggal , Mohak Sukhwani

Reinforcement learning-based control policies have been frequently demonstrated to be more effective than analytical techniques for many manipulation tasks. Commonly, these methods learn neural control policies that predict end-effector…

Robotics · Computer Science 2026-04-22 Hunter L. Brown , Geoffrey Hollinger , Stefan Lee

Robot motion planning involves computing a sequence of valid robot configurations that take the robot from its initial state to a goal state. Solving a motion planning problem optimally using analytical methods is proven to be PSPACE-Hard.…

Robotics · Computer Science 2021-07-26 Naman Shah , Abhyudaya Srinet , Siddharth Srivastava

Legged manipulators extend robotic capabilities beyond static manipulation by integrating agile locomotion with versatile arm control. However, achieving precise manipulation while maintaining coordinated locomotion remains a major…

We introduce an elastic-driven self-folding approach that fabricates robots directly from flat 3D-printed conductive PLA nets. Elastic bands routed through printed hooks store energy that folds the sheet into programmed 3D geometries, while…

Robotics · Computer Science 2026-05-07 Gaolin Ge , Qifeng Yang , Haoran Lu , Tingyu Cheng , Martin Nisser , Yiyue Luo

Robotic assembly in architectural construction faces a persistent bottleneck: existing planners are either highly specialized, requiring prohibitive retraining for every new geometric design, or operationally inefficient, treating…

Machine Learning · Computer Science 2026-05-20 Shih-Yu Lai , Chia-Ching Yen , Yang-Ting Shen , Peter Yichen Chen , Yu-Lun Liu , Bing-Yu Chen

Soft robotic actuators are safe and adaptable devices with inherent compliance, which makes them attractive for manipulating delicate and complex objects. Researchers have integrated stiff materials into soft actuators to increase their…

Robotics · Computer Science 2022-11-15 Gregory M. Campbell , Jessica Yin , Yuyang Song , Umesh Gandhi , Mark Yim , James Pikul

Future operating theatres will be equipped with robots to perform various surgical tasks including, for example, endoscope control. Human-in-the-loop supervisory control architectures where the surgeon selects from several autonomous…

Complex and skillful motions in actual assembly process are challenging for the robot to generate with existing motion planning approaches, because some key poses during the human assembly can be too skillful for the robot to realize…

Robotics · Computer Science 2019-10-07 Yan Wang , Kensuke Harada , Weiwei Wan

When modeling complex robot systems such as branched robots, whose kinematic structures are a tree, current techniques often require modeling the whole structure from scratch, even when partial models for the branches are available. This…

Robotics · Computer Science 2024-07-23 Frederico Fernandes Afonso Silva , Bruno Vilhena Adorno

Impedance control is a well-established technique to control interaction forces in robotics. However, real implementations of impedance control with an inner loop may suffer from several limitations. Although common practice in designing…

Robotic catheterization is typically used for percutaneous coronary intervention procedures nowadays and it involves steering flexible endovascular tools to open up occlusion in the coronaries. In this study, a sample-efficient deep…

Robotics · Computer Science 2021-10-29 Olatunji Mumini Omisore , Toluwanimi Akinyemi , Wenke Duan , Wenjing Du , Lei Wang

Part assembly is a typical but challenging task in robotics, where robots assemble a set of individual parts into a complete shape. In this paper, we develop a robotic assembly simulation environment for furniture assembly. We formulate the…

Robotics · Computer Science 2021-12-21 Mingxin Yu , Lin Shao , Zhehuan Chen , Tianhao Wu , Qingnan Fan , Kaichun Mo , Hao Dong

We present an optimization-based design process that can generate the best insertion-based joints with respect to different errors, including manipulation error, manufacturing error, and sensing error. We separate the analysis into two…

Robotics · Computer Science 2022-11-14 Zhibin Zou

As a widely used method in machine learning, principal component analysis (PCA) shows excellent properties for dimensionality reduction. It is a serious problem that PCA is sensitive to outliers, which has been improved by numerous Robust…

Machine Learning · Computer Science 2020-11-24 Shenglan Liu , Yang Yu