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

Abstract

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.

Task Complexity and the Skills Dilemma in the Programming and Control of Collaborative Robots for Manufacturing

“…While multiple-robot systems (MRS) can reduce the overall complexity of a task, their need for collaboration and accurate coordination [41] can add significantly to the programming workload. Further compounding the technical complexity of MRS is the need to select a suitable task allocation strategy that is robust, scalable and can be optimised for a specific task [42]. A cluster-based approach, centred around the location of tasks relative to team members, allocates tasks by training a binary classifier to nominate one of two task allocation mechanisms through an auction bidding process [43].…”

Routing with Face Traversal and Auctions Algorithms for Task Allocation in WSRN

“…The task allocation strategies can be classified according to their applications [14]. Optimization-and auction-based techniques are described as the most important task allocation strategies [4,5,15].…”

“…Accordingly, the task assignment problem (also known as the task allocation problem) is to find the most suitable robot to respond to the event. This problem is in robotic literature well known as a multirobot task allocation problem, and in [3,4] and [5], are reviewed and presented the existing solutions and their variations in WSRN.…”

Research on dual robot collaboration method based on improved double ant colony algorithm

“…Multi-robot task allocation can effectively schedule robot teams and solve scheduling and negotiation problems for robots in special situations such as working conditions saturation, task conflicts, insufficient capabilities and faults. Therefore, the quality of task allocation strategies greatly affects the operational efficiency and actual performance of multi-robot systems (Janardhanan et al , 2020). The solution to the multi-robot Assignment problem includes a task allocation method based on market mechanism, a task allocation method based on clustering and a heuristic algorithm based on optimization.…”