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The drive for efficiency and safety in construction has boosted the role of robotics and automation. However, complex tasks like welding and pipe insertion pose challenges due to their need for precise adaptive force control, which…

Robotics · Computer Science 2025-01-28 Hengxu You , Yang Ye , Tianyu Zhou , Jing Du

In this paper, we present a principled method to model general planar sliding motion with distributed convex contact patch. The effect of contact patch with indeterminate pressure distribution can be equivalently modeled as the contact…

Robotics · Computer Science 2019-04-18 Jiayin Xie , Nilanjan Chakraborty

Disturbance estimation for Micro Aerial Vehicles (MAVs) is crucial for robustness and safety. In this paper, we use novel, bio-inspired airflow sensors to measure the airflow acting on a MAV, and we fuse this information in an Unscented…

Robotics · Computer Science 2020-03-06 Andrea Tagliabue , Aleix Paris , Suhan Kim , Regan Kubicek , Sarah Bergbreiter , Jonathan P. How

Physical interactive robotics, ranging from wearable devices to collaborative humanoid robots, require close coordination between mechanical design and control. However, evaluating interactive dynamics is challenging due to complex human…

Robotics · Computer Science 2026-03-11 Chenhui Zuo , Jinhao Xu , Michael Qian Vergnolle , Yanan Sui

We report on the injection locking of an optically levitated nanomechanical oscillator (a silica nanosphere) to resonant intensity modulations of an external optical signal. We explore the characteristic features of injection locking in…

In the last decades, the applications of power inverter increased rapidly. As a result, in spite of rectifier, an inverter with a high-power electronic oscillator has capability to convert direct current (DC) into alternating current (AC)…

Systems and Control · Computer Science 2016-08-01 Shou Qiao , Zhao Huio , Xio Tangue

This article presents a multi-physics methodology for the numerical simulation of physical systems that involve the non-linear interaction of multi-phase reactive fluids and elastoplastic solids, inducing high strain-rates and high…

Computational Physics · Physics 2021-06-04 Tim Wallis , Philip T. Barton , Nikolaos Nikiforakis

This paper develops a data-driven inverse reinforcement learning technique for a class of linear systems to estimate the cost function of an agent online, using input-output measurements. A simultaneous state and parameter estimator is…

Systems and Control · Computer Science 2021-07-07 Rushikesh Kamalapurkar

In order to determine indirectly the generalized forces applied on the gearbox, two approaches are tested, one is a numerical method, the other is experimental. For the numerical method, the vibration response of the gearbox can be…

Classical Physics · Physics 2007-05-23 Gu Xiang Zhang , Emmanuel Rigaud , Jean-Claude Pascal , Jean Sabot

Precise perception of contact interactions is essential for fine-grained manipulation skills for robots. In this paper, we present the design of feedback skills for robots that must learn to stack complex-shaped objects on top of each other…

Mechanical interactions between rigid rings and flexible cables find broad application in both daily life (hanging clothes) and engineering systems (closing a tether-net). A reduced-order method for the dynamic analysis of sliding rings on…

Graphics · Computer Science 2024-05-21 Weicheng Huang , Peifei Xu , Zhaowei Liu

A height-function-based numerical approach is developed for enforcing contact angles on flat and curved solid surfaces within two-dimensional volume-of-fluid simulations. This method incorporates the contact line position into the curvature…

Frictional sliding along an interface between two identical isotropic elastic plates under impact shear loading is investigated experimentally and numerically. The plates are held together by a compressive stress and one plate is subject to…

Geophysics · Physics 2009-11-10 D. Coker , G. Lykotrafitis , A. Needleman , A. J. Rosakis

Vision-based tactile sensors have gained extensive attention in the robotics community. The sensors are highly expected to be capable of extracting contact information i.e. haptic information during in-hand manipulation. This nature of…

Robust reinforcement learning agents using high-dimensional observations must be able to identify relevant state features amidst many exogeneous distractors. A representation that captures controllability identifies these state elements by…

Machine Learning · Computer Science 2024-06-25 Max Rudolph , Caleb Chuck , Kevin Black , Misha Lvovsky , Scott Niekum , Amy Zhang

Torque-controlled actuators are critical components in mechatronic systems that closely interact with their environment, such as legged robots, collaborative manipulators, and exoskeletons. The performance and stability of these actuators…

Systems and Control · Electrical Eng. & Systems 2025-05-14 Victor Shime , Elisa G. Vergamini , Cícero Zanette , Leonardo F. dos Santos , Lucca Maitan , Andrea Calanca , Thiago Boaventura

Multi-agent human-robot co-manipulation is a poorly understood process with many inputs that potentially affect agent behavior. This paper explores one such input known as interaction force. Interaction force is potentially a primary…

Robotics · Computer Science 2024-08-06 Kody B. Shaw , Dallin L. Cordon , Marc D. Killpack , John L. Salmon

Soft manipulators are known for their superiority in coping with high-safety-demanding interaction tasks, e.g., robot-assisted surgeries, elderly caring, etc. Yet the challenges residing in real-time contact feedback have hindered further…

Robotics · Computer Science 2024-09-13 Xiaohan Zhu , Ran Bu , Zhen Li , Fan Xu , Hesheng Wang

Elastic materials with holes and inclusions are important in a large variety of contexts ranging from construction material to biological membranes. More recently, they have also been exploited in mechanical metamaterials, where the…

Soft Condensed Matter · Physics 2021-05-26 Siddhartha Sarkar , Matjaz Cebron , Miha Brojan , Andrej Kosmrlj

Intelligent agents need a physical understanding of the world to predict the impact of their actions in the future. While learning-based models of the environment dynamics have contributed to significant improvements in sample efficiency…

Machine Learning · Computer Science 2020-05-20 Eric Heiden , David Millard , Hejia Zhang , Gaurav S. Sukhatme