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Many manipulation tasks require the robot to control the contact between a grasped compliant tool and the environment, e.g. scraping a frying pan with a spatula. However, modeling tool-environment interaction is difficult, especially when…

Robotics · Computer Science 2022-10-11 Mark Van der Merwe , Dmitry Berenson , Nima Fazeli

The fields of soft and bio-inspired robotics promise to imbue synthetic systems with capabilities found in the natural world. However, many of these biological capabilities are yet to be realized. For example, vines in nature direct growth…

Robotics · Computer Science 2023-12-29 Shivani Deglurkar , Charles Xiao , Luke F. Gockowski , Megan T. Valentine , Elliot W. Hawkes

In recent years, there has been a growing demand for improved autonomy for in-orbit operations such as rendezvous, docking, and proximity maneuvers, leading to increased interest in employing Deep Learning-based Spacecraft Pose Estimation…

Computer Vision and Pattern Recognition · Computer Science 2023-11-10 Arunkumar Rathinam , Haytam Qadadri , Djamila Aouada

Many aerial robotic applications require the ability to land on moving platforms, such as delivery trucks and marine research boats. We present a method to autonomously land an Unmanned Aerial Vehicle on a moving vehicle. A visual servoing…

The problem of image-based visual servoing (IBVS) of an aerial robot using deep-learning-based keypoint detection is addressed in this article. A monocular RGB camera mounted on the platform is utilized to collect the visual data. A…

Robotics · Computer Science 2026-04-14 Shayan Sepahvand , Niloufar Amiri , Farrokh Janabi-Sharifi

Robots need robust and flexible vision systems to perceive and reason about their environments beyond geometry. Most of such systems build upon deep learning approaches. As autonomous robots are commonly deployed in initially unknown…

Robotics · Computer Science 2024-10-15 Julius Rückin , Federico Magistri , Cyrill Stachniss , Marija Popović

Robotic skill learning has been increasingly studied but the demonstration collections are more challenging compared to collecting images/videos in computer vision and texts in natural language processing. This paper presents a skill…

Robotics · Computer Science 2023-11-14 Xiangyu Chu , Yunxi Tang , Lam Him Kwok , Yuanpei Cai , Kwok Wai Samuel Au

Object tracking based on retina-inspired and event-based dynamic vision sensor (DVS) is challenging for the noise events, rapid change of event-stream shape, chaos of complex background textures, and occlusion. To address these challenges,…

Computer Vision and Pattern Recognition · Computer Science 2018-03-20 Hongmin Li , Luping Shi

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

Event-based sensors offer significant advantages over traditional frame-based cameras, especially in scenarios involving rapid motion or challenging lighting conditions. However, event data frequently suffers from considerable noise,…

Computer Vision and Pattern Recognition · Computer Science 2025-06-05 Marcin Kowalczyk , Kamil Jeziorek , Tomasz Kryjak

When autonomous systems are deployed in real-world scenarios, sensors are often subject to limited field-of-view (FOV) constraints, either naturally through system design, or through unexpected occlusions or sensor failures. In conditions…

Robotics · Computer Science 2026-02-16 Knut Peterson , David Han

Utilizing perception for feedback control in combination with Dynamic Movement Primitive (DMP)-based motion generation for a robot's end-effector control is a useful solution for many robotic manufacturing tasks. For instance, while…

Robotics · Computer Science 2024-10-28 Ghananeel Rotithor , Iman Salehi , Edward Tunstel , Ashwin P. Dani

This work proposes a fast deployment pipeline for visually-servoed robots which does not assume anything about either the robot - e.g. sizes, colour or the presence of markers - or the deployment environment. In this, accurate estimation of…

Robotics · Computer Science 2023-06-27 Luke Robinson , Daniele De Martini , Matthew Gadd , Paul Newman

Rapid robotic system development sets a demand for multi-disciplinary methods and tools to explore and compare design alternatives. In this paper, we present collaborative modeling that combines discrete-event models of controller software…

Robotics · Computer Science 2018-02-20 Martin Peter Christiansen , Peter Gorm Larsen , Rasmus Nyholm Jørgensen

In this paper, we investigate the stabilization of a nonlinear plant subject to network constraints, under the assumption of partial knowledge of the plant state. The event triggered paradigm is used for the observation and the control of…

Systems and Control · Computer Science 2015-03-16 L. Etienne , S. Di Gennaro , J. -P. Barbot

Collaborative robots are expected to be able to work alongside humans and in some cases directly replace existing human workers, thus effectively responding to rapid assembly line changes. Current methods for programming contact-rich tasks,…

Recently, end-to-end robotic manipulation models have gained significant attention for their generalizability and scalability. However, they often suffer from limited robustness to camera viewpoint changes when training with a fixed camera.…

Robotics · Computer Science 2026-04-24 Songen Gu , Yuhang Zheng , Weize Li , Yupeng Zheng , Yating Feng , Xiang Li , Yilun Chen , Pengfei Li , Wenchao Ding

Event cameras or dynamic vision sensors (DVS) record asynchronous response to brightness changes instead of conventional intensity frames, and feature ultra-high sensitivity at low bandwidth. The new mechanism demonstrates great advantages…

Computer Vision and Pattern Recognition · Computer Science 2024-01-09 Bo Zhang , Yuqi Han , Jinli Suo , Qionghai Dai

Event-based sensors have recently drawn increasing interest in robotic perception due to their lower latency, higher dynamic range, and lower bandwidth requirements compared to standard CMOS-based imagers. These properties make them ideal…

Identifying independently moving objects is an essential task for dynamic scene understanding. However, traditional cameras used in dynamic scenes may suffer from motion blur or exposure artifacts due to their sampling principle. By…

Computer Vision and Pattern Recognition · Computer Science 2022-07-08 Yi Zhou , Guillermo Gallego , Xiuyuan Lu , Siqi Liu , Shaojie Shen