TY - GEN
T1 - Uncertain Local Leader Selection in Distributed Formations
AU - Rovinsky, Dany
AU - Agmon, Noa
N1 - Publisher Copyright: © 2018 IEEE.
PY - 2018/12/27
Y1 - 2018/12/27
N2 - Leader-Follower is a hierarchical form of multi-robot formation control, where each robot aims to maintain specific predefined angle and distance from one or more robots in the team (referred to as its local leaders), while a single robot is selected to lead the entire formation to a desired destination. When the robots are given a specific formation to maintain, their goal is usually to minimize the deviation from this desired formation (maximizing the accuracy) during their journey. Previous work has considered optimality in an uncertain environment only in centralized setting (or using perfect, or almost perfect communication). In this paper we examine the problem of optimal multi-robot formation control in a distributed setting, while accounting for two challenges: sensory uncertainty and absence of communication. Specifically, we present an algorithm that allows each individual robot to estimate the overall formation accuracy of the other robots in their field of view via a tree reconstruction algorithm. The algorithm is used to select the most accurate local leader, or to generate virtual local leader via a weighted average of all visible robots. We provide both theoretical analysis and an extensive empirical evaluation (in ROS/Gazebo simulated environment) showing the effectiveness of the two approaches.
AB - Leader-Follower is a hierarchical form of multi-robot formation control, where each robot aims to maintain specific predefined angle and distance from one or more robots in the team (referred to as its local leaders), while a single robot is selected to lead the entire formation to a desired destination. When the robots are given a specific formation to maintain, their goal is usually to minimize the deviation from this desired formation (maximizing the accuracy) during their journey. Previous work has considered optimality in an uncertain environment only in centralized setting (or using perfect, or almost perfect communication). In this paper we examine the problem of optimal multi-robot formation control in a distributed setting, while accounting for two challenges: sensory uncertainty and absence of communication. Specifically, we present an algorithm that allows each individual robot to estimate the overall formation accuracy of the other robots in their field of view via a tree reconstruction algorithm. The algorithm is used to select the most accurate local leader, or to generate virtual local leader via a weighted average of all visible robots. We provide both theoretical analysis and an extensive empirical evaluation (in ROS/Gazebo simulated environment) showing the effectiveness of the two approaches.
UR - http://www.scopus.com/inward/record.url?scp=85062975009&partnerID=8YFLogxK
U2 - https://doi.org/10.1109/iros.2018.8594307
DO - https://doi.org/10.1109/iros.2018.8594307
M3 - منشور من مؤتمر
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 4818
EP - 4824
BT - 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018
Y2 - 1 October 2018 through 5 October 2018
ER -