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相关论文: Challenges and Opportunities for Large-Scale Explo…

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While much research explores improving robot capabilities, there is a deficit in researching how robots are expected to perform tasks safely, especially in high-risk problem domains. Robots must earn the trust of human operators in order to…

Multi-robot systems are an efficient method to explore and map an unknown environment. The simulataneous localization and mapping (SLAM) algorithm is common for single robot systems, however multiple robots can share respective map data in…

机器人学 · 计算机科学 2021-02-03 Henry Fielding Cappel

In planning for future human space exploration, it is important to consider how to design for uplifting interpersonal communications and social dynamics among crew members. What if embodied social robots could help to improve the overall…

机器人学 · 计算机科学 2021-05-19 Huili Chen , Cynthia Breazeal

We present SpaceAgents-1, a system for learning human and multi-robot collaboration (HMRC) strategies under microgravity conditions. Future space exploration requires humans to work together with robots. However, acquiring proficient robot…

机器人学 · 计算机科学 2024-02-23 Miao Xin , Zhongrui You , Zihan Zhang , Taoran Jiang , Tingjia Xu , Haotian Liang , Guojing Ge , Yuchen Ji , Shentong Mo , Jian Cheng

In this paper we consider the problem of coordinating robotic systems with different kinematics, sensing and vision capabilities to achieve certain mission goals. An approach that makes use of a heterogeneous team of agents has several…

机器人学 · 计算机科学 2015-09-04 Nicola Bezzo , Joshua P. Hecker , Karl Stolleis , Melanie E. Moses , Rafael Fierro

In this article, we introduce a novel strategy for robotic exploration in unknown environments using a semantic topometric map. As it will be presented, the semantic topometric map is generated by segmenting the grid map of the currently…

机器人学 · 计算机科学 2024-06-27 Scott Fredriksson , Akshit Saradagi , George Nikolakopoulos

This paper introduces a multirobot cooperation approach to solve the "pursuit evasion" problem for mobile robots that have omnidirectional vision sensors. The main characteristic of this approach is to implement a real cooperation between…

人工智能 · 计算机科学 2018-10-22 Damien Pellier , Humbert Fiorino

This paper develops a methodology for collaborative human-robot exploration that leverages implicit coordination. Most autonomous single- and multi-robot exploration systems require a remote operator to provide explicit guidance to the…

机器人学 · 计算机科学 2023-04-20 Yves Georgy Daoud , Kshitij Goel , Nathan Michael , Wennie Tabib

With the real need of field exploration in large-scale and extreme outdoor environments, cooperative exploration tasks have garnered increasing attention. This paper presents a comprehensive review of multi-robot cooperative exploration…

For robots to navigate and interact more richly with the world around them, they will likely require a deeper understanding of the world in which they operate. In robotics and related research fields, the study of understanding is often…

When individual robots have limited sensing capabilities or insufficient fault tolerance, it becomes necessary for multiple robots to form teams during exploration, thereby increasing the collective observation range and reliability.…

机器人学 · 计算机科学 2026-03-06 Hiroaki Kawashima , Shun Ikejima , Takeshi Takai , Mikita Miyaguchi , Yasuharu Kunii

Heterogeneous multi-robot systems are advantageous for operations in unknown environments because functionally specialised robots can gather environmental information, while others perform tasks. We define this decomposition as the…

Robotic exploration of unknown environments is fundamentally a problem of decision making under uncertainty where the robot must account for uncertainty in sensor measurements, localization, action execution, as well as many other factors.…

Heterogeneous multirobot systems show great potential in complex tasks requiring coordinated hybrid cooperation. However, existing methods that rely on static or task-specific models often lack generalizability across diverse tasks and…

机器人学 · 计算机科学 2025-10-28 Haokun Liu , Zhaoqi Ma , Yunong Li , Junichiro Sugihara , Yicheng Chen , Jinjie Li , Moju Zhao

This work presents a 3D multi-robot exploration framework for a team of UGVs moving on uneven terrains. The framework was designed by casting the two-level coordination strategy presented in [1] into the context of multi-robot exploration.…

机器人学 · 计算机科学 2023-07-10 Luigi Freda , Tiago Novo , David Portugal , Rui P. Rocha

Current technological advances open up new opportunities for bringing human-machine interaction to a new level of human-centered cooperation. In this context, a key issue is the semantic understanding of the environment in order to enable…

机器人学 · 计算机科学 2022-11-08 Thorsten Hempel , Marc-André Fiedler , Aly Khalifa , Ayoub Al-Hamadi , Laslo Dinges

In this paper, we describe the development of symbolic representations annotated on human-robot dialogue data to make dimensions of meaning accessible to autonomous systems participating in collaborative, natural language dialogue, and to…

Multi-robot rendezvous and exploration are fundamental challenges in the domain of mobile robotic systems. This paper addresses multi-robot rendezvous within an initially unknown environment where communication is only possible after the…

机器人学 · 计算机科学 2024-07-22 Mauro Tellaroli , Matteo Luperto , Michele Antonazzi , Nicola Basilico

To achieve autonomy in complex real-world exploration missions, we consider deployment strategies for a team of robots with heterogeneous autonomy capabilities. In this work, we formulate a multi-robot exploration mission and compute an…

机器人学 · 计算机科学 2024-11-04 Muhammad Fadhil Ginting , Kyohei Otsu , Mykel J. Kochenderfer , Ali-akbar Agha-mohammadi

This paper develops a communication-efficient distributed mapping approach for rapid exploration of a cave by a multi-robot team. Subsurface planetary exploration is an unsolved problem challenged by communication, power, and compute…

机器人学 · 计算机科学 2024-04-18 Kshitij Goel , Wennie Tabib , Nathan Michael