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Similarly, secondary task allocation successfully identifies and selects worker robots.
Task allocation mechanisms are employed by multi-robot systems to efficiently distribute tasks between different robots.
A multi-robot mapping and exploration task is utilised as a model task to evaluate the task allocation process.
Task allocation to groups of agents is necessary when tasks cannot be performed by a single agent.
Currently, many task allocation methods rely on detailed expert knowledge to coordinate robots.
We employ a simple task allocation strategy that allows a swarm of robots to behaviorally specialize.
Both task allocation processes are also robust to parameter variation permitting intuitive selection of parameter values.
Experiments show that primary task allocation is able to successfully identify and select manager robots.
Each component protocol is activated to address priority-based allocation, resource-aware allocation, and task re-allocation at a different task administration context, ranging from task initialization, task allocation, to task monitoring, respectively.
This paper proposes a resource-based task allocation algorithm for multi-robot systems.
New technology can also provide an impetus for innovation in task allocation.
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