Delegation of Task Allocation Authority and the Value of Communication when Performance Measures are Imperfect

2019 ◽  
Author(s):  
Anna Rohlfing-Bastian ◽  
Anja Schöttner
Keyword(s):  
Performance Measures ◽  
Task Allocation

scholarly journals Multi-objective Optimisation of Multi-robot Task Allocation with Precedence Constraints

2018 ◽  
Vol 68 (2) ◽  
pp. 175 ◽  
Author(s):  
Padmanabhan Panchu K. ◽  
M. Rajmohan ◽  
R. Sundar ◽  
R. Baskaran
Keyword(s):  
Performance Measures ◽  
Task Allocation ◽  
Optimal Allocation ◽  
Optimal Number ◽  
Precedence Constraints ◽  
Good Convergence ◽  
Robot Task ◽  
Almost All ◽  
Taguchi’S Design Of Experiments ◽  
Multi Robot

Efficacy of the multi-robot systems depends on proper sequencing and optimal allocation of robots to the tasks. Focuses on deciding the optimal allocation of set-of-robots to a set-of-tasks with precedence constraints considering multiple objectives. Taguchi’s design of experiments based parameter tuned genetic algorithm (GA) is developed for generalised task allocation of single-task robots to multi-robot tasks. The developed methodology is tested for 16 scenarios by varying the number of robots and number of tasks. The scenarios were tested in a simulated environment with a maximum of 20 robots and 40 multi-robot foraging tasks. The tradeoff between performance measures for the allocations obtained through GA for different task levels was used to decide the optimal number of robots. It is evident that the tradeoffs occur at 20 per cent of performance measures and the optimal number of robot varies between 10 and 15 for almost all the task levels. This method shows good convergence and found that the precedence constraints affect the optimal number of robots required for a particular task level.

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