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The problem of cooperative localization for a small group of Unmanned Aerial Vehicles (UAVs) in a GNSS denied environment is addressed in this paper. The presented approach contains two sequential steps: first, an algorithm called…

系统与控制 · 电气工程与系统科学 2020-06-11 Chizhao Yang , Jared Strader , Yu Gu , Aaron Canciani , Kevin Brink

This paper addresses a safe planning and control problem for mobile robots operating in communication- and sensor-limited dynamic environments. In this case the robots cannot sense the objects around them and must instead rely on…

机器人学 · 计算机科学 2022-09-13 Matthew Cleaveland , Esen Yel , Yiannis Kantaros , Insup Lee , Nicola Bezzo

For effective autonomous navigation,estimation of the pose of the robot is essential at every sampling time. For computing an accurate estimation,odometric error needs to be reduced with the help of data from external sensor. In this work,…

计算机视觉与模式识别 · 计算机科学 2012-12-07 Debajyoti Banerji , Ranjit Ray , Jhankar Basu , Indrajit Basak

Autonomous aerial robots are increasingly being deployed in real-world scenarios, where transparent glass obstacles present significant challenges to reliable navigation. Researchers have investigated the use of non-contact sensors and…

机器人学 · 计算机科学 2025-05-12 Xinyi Chen , Yichen Zhang , Hetai Zou , Junzhe Wang , Shaojie Shen

This paper presents a provably correct method for robot navigation in 2D environments cluttered with familiar but unexpected non-convex, star-shaped obstacles as well as completely unknown, convex obstacles. We presuppose a limited range…

机器人学 · 计算机科学 2018-10-30 Vasileios Vasilopoulos , Daniel E. Koditschek

Relative localization between autonomous robots without infrastructure is crucial to achieve their navigation, path planning, and formation in many applications, such as emergency response, where acquiring a prior knowledge of the…

Controlling a team of robots in a coordinated manner is challenging because centralized approaches (where all computation is performed on a central machine) scale poorly, and globally referenced external localization systems may not always…

机器人学 · 计算机科学 2026-02-20 Abhishek Goudar , Angela P. Schoellig

While autonomous multi-robots can achieve safe and coordinated navigation, they often struggle to adapt to unforeseen conditions and to capture operator-driven objectives in unstructured environments. We present a Virtual Reality (VR)-based…

Recently, the progress in the radar sensing technology consisting in the miniaturization of the packages and increase in measuring precision has drawn the interest of the robotics research community. Indeed, a crucial task enabling autonomy…

机器人学 · 计算机科学 2026-02-05 Jan Michalczyk

Many works in collaborative robotics and human-robot interaction focuses on identifying and predicting human behaviour while considering the information about the robot itself as given. This can be the case when sensors and the robot are…

We present the results of experiments performed using a team of small autonomous underwater vehicles (AUVs) to determine the location of an isobath. The primary contributions of this work are (1) the development of a novel objective…

机器人学 · 计算机科学 2024-12-30 Benjamin Biggs , Daniel J. Stilwell , Harun Yetkin , James McMahon

Scene reconstruction is an essential capability for underwater robots navigating in close proximity to structures. Monocular vision-based reconstruction methods are unreliable in turbid waters and lack depth scale information. Sonars are…

机器人学 · 计算机科学 2026-03-17 Ivana Collado-Gonzalez , John McConnell , Paul Szenher , Brendan Englot

Recent work has shown impressive localization performance using only images of ground textures taken with a downward facing monocular camera. This provides a reliable navigation method that is robust to feature sparse environments and…

机器人学 · 计算机科学 2023-03-13 Kyle M. Hart , Brendan Englot , Ryan P. O'Shea , John D. Kelly , David Martinez

Robots will bring search and rescue (SaR) in disaster response to another level, in case they can autonomously take over dangerous SaR tasks from humans. A main challenge for autonomous SaR robots is to safely navigate in cluttered…

机器人学 · 计算机科学 2025-05-07 Karlo Rado , Mirko Baglioni , Anahita Jamshidnejad

Object detection aims to obtain the location and the category of specific objects in a given image, which includes two tasks: classification and location. In recent years, researchers tend to apply object detection to underwater robots…

计算机视觉与模式识别 · 计算机科学 2025-03-27 Pinhao Song

In public spaces shared with humans, ensuring multi-robot systems navigate without collisions while respecting social norms is challenging, particularly with limited communication. Although current robot social navigation techniques…

机器人学 · 计算机科学 2024-05-17 Weizheng Wang , Le Mao , Ruiqi Wang , Byung-Cheol Min

Autonomous aerial robots are increasingly being deployed in real-world scenarios, where transparent obstacles present significant challenges to reliable navigation and mapping. These materials pose a unique problem for traditional…

机器人学 · 计算机科学 2025-10-09 Malakhi Hopkins , Varun Murali , Vijay Kumar , Camillo J Taylor

Accurate localisation in planetary robotics enables the advanced autonomy required to support the increased scale and scope of future missions. The successes of the Ingenuity helicopter and multiple planetary orbiters lay the groundwork for…

计算机视觉与模式识别 · 计算机科学 2026-04-30 Lachlan Holden , Feras Dayoub , Alberto Candela , David Harvey , Tat-Jun Chin

In order to keep aquatic ecosystems safe and healthy, it is imperative that cleaning be done frequently. This research suggests the use of autonomous underwater rovers for effective underwater cleaning as a novel approach to this issue. The…

机器人学 · 计算机科学 2023-04-18 Aditya Sundarajan , Jaideepnath Anand , Kevin Timothy Muller , Mangal Das

Manipulation in confined and cluttered environments remains a significant challenge due to partial observability and complex configuration spaces. Effective manipulation in such environments requires an intelligent exploration strategy to…

机器人学 · 计算机科学 2026-05-20 Qixuan Li , Chen Le , Dongyue Huang , Jincheng Yu , Xinlei Chen