Gini coefficient-based task allocation for multi-robot systems with limited energy resources

2018 ◽  
Vol 5 (1) ◽  
pp. 155-168 ◽  
Author(s):  
Danfeng Wu ◽  
Guangping Zeng ◽  
Lingguo Meng ◽  
Weijian Zhou ◽  
Linmin Li
Keyword(s):  
Gini Coefficient ◽  
Task Allocation ◽  
Energy Resources ◽  
Limited Energy ◽  
Robot Systems ◽  
Multi Robot

scholarly journals Resilient Task Allocation in Heterogeneous Multi-Robot Systems

2021 ◽  
Vol 6 (2) ◽  
pp. 1327-1334
Author(s):  
Siddharth Mayya ◽  
Diego S. D'antonio ◽  
David Saldana ◽  
Vijay Kumar
Keyword(s):  
Task Allocation ◽  
Robot Systems ◽  
Multi Robot

A Novel Approach With Bayesian Networks to Multi-Robot Task Allocation in Dynamic Environments

2021 ◽  
Author(s):  
Ching-Wei Chuang ◽  
Harry H. Cheng
Keyword(s):  
Bayesian Networks ◽  
Task Allocation ◽  
Low Cost ◽  
Dynamic Environments ◽  
Modern World ◽  
Robot System ◽  
Novel Approach ◽  
Robot Systems ◽  
Robot Task ◽  
Multi Robot

Abstract In the modern world, building an autonomous multi-robot system is essential to coordinate and control robots to help humans because using several low-cost robots becomes more robust and efficient than using one expensive, powerful robot to execute tasks to achieve the overall goal of a mission. One research area, multi-robot task allocation (MRTA), becomes substantial in a multi-robot system. Assigning suitable tasks to suitable robots is crucial in coordination, which may directly influence the result of a mission. In the past few decades, although numerous researchers have addressed various algorithms or approaches to solve MRTA problems in different multi-robot systems, it is still difficult to overcome certain challenges, such as dynamic environments, changeable task information, miscellaneous robot abilities, the dynamic condition of a robot, or uncertainties from sensors or actuators. In this paper, we propose a novel approach to handle MRTA problems with Bayesian Networks (BNs) under these challenging circumstances. Our experiments exhibit that the proposed approach may effectively solve real problems in a search-and-rescue mission in centralized, decentralized, and distributed multi-robot systems with real, low-cost robots in dynamic environments. In the future, we will demonstrate that our approach is trainable and can be utilized in a large-scale, complicated environment. Researchers might be able to apply our approach to other applications to explore its extensibility.

scholarly journals Analysis of Dynamic Task Allocation in Multi-Robot Systems

2006 ◽  
Author(s):  
Kristina Lerman ◽  
Chris Jones ◽  
Aram Galstyan ◽  
Maja J. Mataric
Keyword(s):  
Task Allocation ◽  
Dynamic Task ◽  
Dynamic Task Allocation ◽  
Robot Systems ◽  
Multi Robot

Review on state-of-the-art dynamic task allocation strategies for multiple-robot systems

2020 ◽  
Vol 47 (6) ◽  
pp. 929-942
Author(s):  
Seenu N. ◽  
Kuppan Chetty R.M. ◽  
Ramya M.M. ◽  
Mukund Nilakantan Janardhanan
Keyword(s):  
Task Allocation ◽  
State Of The Art ◽  
Objective Functions ◽  
Research Directions ◽  
Content Type ◽  
Dynamic Task ◽  
Dynamic Task Allocation ◽  
Robot Systems ◽  
Allocation Strategies ◽  
Multi Robot

Purpose This paper aims to present a concise review on the variant state-of-the-art dynamic task allocation strategies. It presents a thorough discussion about the existing dynamic task allocation strategies mainly with respect to the problem application, constraints, objective functions and uncertainty handling methods. Design/methodology/approach This paper briefs the introduction of multi-robot dynamic task allocation problem and discloses the challenges that exist in real-world dynamic task allocation problems. Numerous task allocation strategies are discussed in this paper, and it establishes the characteristics features between them in a qualitative manner. This paper also exhibits the existing research gaps and conducive future research directions in dynamic task allocation for multiple mobile robot systems. Findings This paper concerns the objective functions, robustness, task allocation time, completion time, and task reallocation feature for performance analysis of different task allocation strategies. It prescribes suitable real-world applications for variant task allocation strategies and identifies the challenges to be resolved in multi-robot task allocation strategies. Originality/value This paper provides a comprehensive review of dynamic task allocation strategies and incites the salient research directions to the researchers in multi-robot dynamic task allocation problems. This paper aims to summarize the latest approaches in the application of exploration problems.

Balancing task allocation in multi-robot systems using K -means clustering and auction based mechanisms

2011 ◽  
Vol 38 (6) ◽  
pp. 6486-6491 ◽  
Author(s):  
Murugappan Elango ◽  
Subramanian Nachiappan ◽  
Manoj Kumar Tiwari
Keyword(s):  
Task Allocation ◽  
Robot Systems ◽  
Multi Robot
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