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We investigate the autonomous navigation of a mobile robot in the presence of other moving vehicles under time-varying uncertain environmental disturbances. We first predict the future state distributions of other vehicles to account for…

Robotics · Computer Science 2020-09-09 Junhong Xu , Kai Yin , Lantao Liu

A team consisting of an unknown number of mobile agents, starting from different nodes of an unknown network, possibly at different times, have to meet at the same node. Agents are anonymous (identical), execute the same deterministic…

Data Structures and Algorithms · Computer Science 2016-03-15 Yoann Dieudonné , Andrzej Pelc

This paper investigates the resilient control, analysis, recovery, and operation of mobile robot networks in time-varying formation tracking under deception attacks on global positioning. Local and global tracking control algorithms are…

Robotics · Computer Science 2021-10-22 Yen-Chen Liu , Kai-Yuan Liu , Zhuoyuan Song

Distributed learning has emerged as a leading paradigm for training large machine learning models. However, in real-world scenarios, participants may be unreliable or malicious, posing a significant challenge to the integrity and accuracy…

Machine Learning · Computer Science 2024-06-10 Grigory Malinovsky , Peter Richtárik , Samuel Horváth , Eduard Gorbunov

In this paper, we present the design and implementation of a robust motion formation distributed control algorithm for a team of mobile robots. The primary task for the team is to form a geometric shape, which can be freely translated and…

Robotics · Computer Science 2018-09-21 Hector Garcia de Marina , Johan Siemonsma , Bayu Jayawardhana , Ming Cao

For planning an assembly of a product from a given set of parts, robots necessitate certain cognitive skills: high-level planning is needed to decide the order of actuation actions, while geometric reasoning is needed to check the…

Artificial Intelligence · Computer Science 2026-05-14 Momina Rizwan , Volkan Patoglu , Esra Erdem

In multi-robot systems (MRS), cooperative localization is a crucial task for enhancing system robustness and scalability, especially in GPS-denied or communication-limited environments. However, adversarial attacks, such as sensor…

Robotics · Computer Science 2025-07-10 Tohid Kargar Tasooji , Ramviyas Parasuraman

Byzantine robustness is an essential feature of algorithms for certain distributed optimization problems, typically encountered in collaborative/federated learning. These problems are usually huge-scale, implying that communication…

Optimization and Control · Mathematics 2024-03-12 Ahmad Rammal , Kaja Gruntkowska , Nikita Fedin , Eduard Gorbunov , Peter Richtárik

Collective decision-making is an essential capability of large-scale multi-robot systems to establish autonomy on the swarm level. A large portion of literature on collective decision-making in swarm robotics focuses on discrete decisions…

Robotics · Computer Science 2023-09-28 Mohsen Raoufi , Pawel Romanczuk , Heiko Hamann

Collaborative localization is an essential capability for a team of robots such as connected vehicles to collaboratively estimate object locations from multiple perspectives with reliant cooperation. To enable collaborative localization,…

Robotics · Computer Science 2021-11-09 Peng Gao , Brian Reily , Rui Guo , Hongsheng Lu , Qingzhao Zhu , Hao Zhang

This paper studies the problem of having mobile robots in a multi-robot system maintain an estimate of the relative position and relative orientation of near-by robots in the environment. This problem is studied in the context of large…

Robotics · Computer Science 2013-12-09 Alejandro Cornejo , Radhika Nagpal

We study the rendezvous problem for two robots moving in the plane (or on a line). Robots are autonomous, anonymous, oblivious, and carry colored lights that are visible to both. We consider deterministic distributed algorithms in which…

Multiagent Systems · Computer Science 2012-11-28 Giovanni Viglietta

Rendezvous aims at gathering all robots at a specific location, which is an important collaborative behavior for multi-robot systems. However, in an unknown environment, it is challenging to achieve rendezvous. Previous researches mainly…

Robotics · Computer Science 2024-12-04 Kun Song , Gaoming Chen , Wenhang Liu , Zhenhua Xiong

Environment perception is a crucial ability for robot's interaction into an environment. One of the first steps in this direction is the combined problem of simultaneous localization and mapping (SLAM). A new method, called G-SLAM, is…

Robotics · Computer Science 2016-07-19 Nikos Zikos , Vassilios Petridis

Bearing measurements,as the most common modality in nature, have recently gained traction in multi-robot systems to enhance mutual localization and swarm collaboration. Despite their advantages, challenges such as sensory noise, obstacle…

Robotics · Computer Science 2024-01-17 Yingjian Wang , Xiangyong Wen , Fei Gao

This paper aims to solve the coordination of a team of robots traversing a route in the presence of adversaries with random positions. Our goal is to minimize the overall cost of the team, which is determined by (i) the accumulated risk…

Robotics · Computer Science 2024-08-22 Zechen Hu , Manshi Limbu , Daigo Shishika , Xuesu Xiao , Xuan Wang

In this work, we explore emergent behaviors by swarms of anonymous, homogeneous, non-communicating, reactive robots that do not know their global position and have limited relative sensing. We introduce a novel method that enables such…

Robotics · Computer Science 2018-04-19 Mario Coppola , Jian Guo , Eberhard K. A. Gill , Guido C. H. E. de Croon

We consider a distributed system of n identical mobile robots operating in the two dimensional Euclidian plane. As in the previous studies, we consider the robots to be anonymous, oblivious, dis-oriented, and without any communication…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-11-14 Shantanu Das , Giuseppe A. Di Luna , Paola Flocchini , Nicola Santoro , Giovanni Viglietta , Masafumi Yamashita

In distributed learning systems, robustness issues may arise from two sources. On one hand, due to distributional shifts between training data and test data, the trained model could exhibit poor out-of-sample performance. On the other hand,…

Machine Learning · Computer Science 2022-11-01 Guanqiang Zhou , Ping Xu , Yue Wang , Zhi Tian

Consider an asynchronous network in a shared-memory environment consisting of n nodes. Assume that up to f of the nodes might be Byzantine (n > 12f), where the adversary is full-information and dynamic (sometimes called adaptive). In…

Distributed, Parallel, and Cluster Computing · Computer Science 2010-07-15 Ezra N. Hoch , Michael Ben-Or , Danny Dolev