Hierarchical multi-robot strategies synthesis and optimization under individual and collaborative temporal logic specifications

This paper presents a hierarchical framework for multi-robot temporal logic task planning. We assume that each robot has its individual task specification and the robots have to jointly satisfy a global collaborative task specification, both described in finite linear temporal logic. To reduce the o...

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Bibliographic Details
Main Authors: Bai, R. (Author), Liu, M. (Author), Xu, Y. (Author), Zhang, S. (Author), Zheng, R. (Author)
Format: Article
Language:English
Published: Elsevier B.V. 2022
Subjects:
Online Access:View Fulltext in Publisher
LEADER 02556nam a2200433Ia 4500
001 0.1016-j.robot.2022.104085
008 220421s2022 CNT 000 0 und d
020 |a 09218890 (ISSN) 
245 1 0 |a Hierarchical multi-robot strategies synthesis and optimization under individual and collaborative temporal logic specifications 
260 0 |b Elsevier B.V.  |c 2022 
856 |z View Fulltext in Publisher  |u https://doi.org/10.1016/j.robot.2022.104085 
520 3 |a This paper presents a hierarchical framework for multi-robot temporal logic task planning. We assume that each robot has its individual task specification and the robots have to jointly satisfy a global collaborative task specification, both described in finite linear temporal logic. To reduce the overall computational complexity, a central server firstly extracts and decomposes a collaborative task sequence from the automaton corresponding to the collaborative task specification, and allocates the subtasks in the sequence to robots. The robots then synthesize their initial execution strategies based on locally constructed product automatons, which integrate task requirements of the assigned collaborative tasks and their individual task specifications. Further, to reduce robots’ wait time in collaborations, we propose a distributed execution strategy adjusting mechanism to iteratively improve the time efficiency of robots. Finally, we prove the completeness of the proposed framework under assumptions, and analyze its time complexity and optimality. Extensive simulation results verify the scalability and optimization efficiency of the proposed method. © 2022 Elsevier B.V. 
650 0 4 |a Collaborative tasks 
650 0 4 |a Computer circuits 
650 0 4 |a Efficiency 
650 0 4 |a Execution strategies 
650 0 4 |a Industrial robots 
650 0 4 |a Iterative methods 
650 0 4 |a Linear temporal logic 
650 0 4 |a Linear temporal logic 
650 0 4 |a Multipurpose robots 
650 0 4 |a Multi-robot 
650 0 4 |a Multi-robot strategy 
650 0 4 |a Multirobots 
650 0 4 |a Robot programming 
650 0 4 |a Specifications 
650 0 4 |a Strategy optimization 
650 0 4 |a Strategy synthesis 
650 0 4 |a Task planning 
650 0 4 |a Task planning 
650 0 4 |a Task specifications 
650 0 4 |a Temporal logic 
650 0 4 |a Temporal logic specifications 
700 1 0 |a Bai, R.  |e author 
700 1 0 |a Liu, M.  |e author 
700 1 0 |a Xu, Y.  |e author 
700 1 0 |a Zhang, S.  |e author 
700 1 0 |a Zheng, R.  |e author 
773 |t Robotics and Autonomous Systems