Coalition-Based Approach to Task Allocation of Multiple Robots With Resource Constraints

2012 ◽  
Vol 9 (3) ◽  
pp. 516-528 ◽  
Author(s):  
Jian Chen ◽  
Dong Sun
2014 ◽  
Vol 77 (3-4) ◽  
pp. 611-627 ◽  
Author(s):  
Min-Hyuk Kim ◽  
Hyeoncheol Baik ◽  
Seokcheon Lee

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 17841-17850 ◽  
Author(s):  
Liwei Huang ◽  
Hong Qu ◽  
Lin Zuo

2017 ◽  
Vol 864 ◽  
pp. 242-248
Author(s):  
Jun Gang Liu ◽  
Guo Jun Huang

Refer to the task allocating and optimization problem of distributed gas-electric hybrid control system, this paper establishes graph model of system hardware structure and application event of the distributed real-time control. The task allocation in distributed application process is abstract as mapping between those two sets. A task allocation scheme of minimum load bus is proposed from the angles of system bus and message mapping. Combined with the design of the gas-electric hybrid power system, genetic algorithm is adopted to solve the optimization problem, and the program verification and the bus analysis are carried out on the experimental bench. The test results show that the proposed scheme can satisfy all kinds of task constraints and resource constraints, the efficiency of the bus is improved, and consumption of resources is reduced.


2018 ◽  
Vol 12 (4) ◽  
pp. 3877-3880 ◽  
Author(s):  
Liang Ren ◽  
Yingying Yu ◽  
Zhiqiang Cao ◽  
Zhiyong Wu ◽  
Junzhi Yu ◽  
...  

2021 ◽  
Vol 59 ◽  
pp. 310-319
Author(s):  
M. De Ryck ◽  
D. Pissoort ◽  
T. Holvoet ◽  
E. Demeester

Robotica ◽  
2013 ◽  
Vol 31 (6) ◽  
pp. 923-934 ◽  
Author(s):  
Rongxin Cui ◽  
Ji Guo ◽  
Bo Gao

SUMMARYThis paper investigates task allocation for multiple robots by applying the game theory-based negotiation approach. Based on the initial task allocation using a contract net-based approach, a new method to select the negotiation robots and construct the negotiation set is proposed by employing the utility functions. A negotiation mechanism suitable for the decentralized task allocation is also presented. Then, a game theory-based negotiation strategy is proposed to achieve the Pareto-optimal solution for the task reallocation. Extensive simulation results are provided to show that the task allocation solutions after the negotiation are better than the initial contract net-based allocation. In addition, experimental results are further presented to show the effectiveness of the approach presented.


2021 ◽  
Vol 12 (1) ◽  
pp. 272
Author(s):  
Bumjin Park ◽  
Cheongwoong Kang ◽  
Jaesik Choi

This paper deals with the concept of multi-robot task allocation, referring to the assignment of multiple robots to tasks such that an objective function is maximized. The performance of existing meta-heuristic methods worsens as the number of robots or tasks increases. To tackle this problem, a novel Markov decision process formulation for multi-robot task allocation is presented for reinforcement learning. The proposed formulation sequentially allocates robots to tasks to minimize the total time taken to complete them. Additionally, we propose a deep reinforcement learning method to find the best allocation schedule for each problem. Our method adopts the cross-attention mechanism to compute the preference of robots to tasks. The experimental results show that the proposed method finds better solutions than meta-heuristic methods, especially when solving large-scale allocation problems.


Author(s):  
Seohyun Jeon ◽  
Minsu Jang ◽  
Daeha Lee ◽  
Young-Jo Cho ◽  
Jaehong Kim ◽  
...  

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