Multiple Leader Candidate and Competitive Position Allocation for Robust Formation against Member Robot Faults

Abstract

This paper proposes a Multiple Leader Candidate (MLC) structure and a Competitive Position Allocation (CPA) algorithm which can be applicable for various applications including environmental sensing. Unlike previous formation structures such as virtual-leader and actual-leader structures with position allocation including a rigid allocation and an optimization based allocation, the formation employing the proposed MLC structure and CPA algorithm is robust against the fault (or disappearance) of the member robots and reduces the entire cost. In the MLC structure, a leader of the entire system is chosen among leader candidate robots. The CPA algorithm is the decentralized position allocation algorithm that assigns the robots to the vertex of the formation via the competition of the adjacent robots. The numerical simulations and experimental results are included to show the feasibility and the performance of the multiple robot system employing the proposed MLC structure and the CPA algorithm.

Effects of Initial Attitude Estimation Errors on Loosely Coupled Smartphone GPS/IMU Integration System

“…In various fields, the Global Positioning System (GPS) and inertial measurement unit (IMU) are used for navigation in numerous applications such as autonomous vehicles [1][2][3][4] and robots [5][6][7][8]. GPS is a global satellitebased navigation system that provides position, velocity, and timing solutions with long-term stability and zero accumulation of errors in time when four or more visible satellites are present [9][10][11].…”