RETRACTED: A decentralized multi-agent control approach for robust robot plan execution

Abstract

Table 2 on page 11, which presents the comparison results between the multi-agent approach and two traditional approaches. In the initial experiments, errors in module design and programming resulted in inefficiencies in the programs written with object-oriented and componentbased approaches, which introduce significant bias in the time cost and code amounts and therefore compromises the findings. The corresponding author offered the explanation that after the case study was repeated by proficient robot engineers, it was established that both object and component models can abstract the robot program well. The comparison criterions of time costs and program amount cannot clearly distinguish which control approach is better. As the evaluation of such criterions is biased and subjective, the presented results lose their confidence. The authors intend to conduct further experimentation to more objectively evaluate the comparative performances of their proposed control approach.

Decentralized Adaptive Control for Quasi-Consensus in Heterogeneous Nonlinear Multiagent Systems

“…Collaborative control of multiagent systems (MASs) has become a research hotspot of distributed artificial intelligence because of its wide application in intelligent energy, multirobot formation, intelligent transportation, multiunmanned system collaboration, and other engineering systems [1][2][3][4][5].…”

“…However, the aforesaid works [1][2][3][4][5][6][7][8][9][10][11][12][13][14] on the consensus of MASs mainly concentrate upon the case in which an agent has the same dynamics as all the neighbors or the leader. In some real scenes, the mismatched parameters or dynamical differences among agents may be almost inevitable, which will thus result in heterogeneous (or nonidentical) multiagent systems (HMASs) [15][16][17].…”

Fast terminal sliding mode control for a nonlinear multi-agent robot system with disturbance

“…Recently, numerous articles have focused on the multiagent robotics systems (Afanasyev et al, 2019;Akhtar & Missen, 2015;Chen et al, 2010;Li et al, 2019;Liu & Wu, 2018;Nazarova & Zhai, 2019;Serebrenny & Shereuzhev, 2020;Tang et al, 2015;Vorotnikov et al, 2018;Wu et al, 2018). A set of principles for multi-agent robotic systems control has been described in Vorotnikov et al (2018).…”