In this paper, we present a heuristic, called nearest-neighbor based Clustering And Routing (nCAR) , which has better execution time compared to the state-of- ...
Abstract— In modern warehouses, robots are being deployed to perform complex tasks such as fetching a set of objects from various locations in a warehouse ...
This paper proposes a novel graph deep-reinforcement-learning-based approach, which solves the problem through learning.
This paper focuses on the tasks where robots fetch outgoing objects from their respective storage racks and bring them to the packaging dock. This requires a ...
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1 day ago · The case study is based on a real Industry 4.0 scenario, where the layout restricts each robotic arm's access, requiring strategic buffer ...
Abstract—We propose a game-theoretic multi-robot task allocation framework that enables a large team of robots to op- timally allocate tasks in dynamically ...
Robots and tasks are defined and ranked in a game according to their Shapley value. •. An algorithm is proposed to group the players into balanced clusters. •.
With this method, tasks are allocated based on a consensus algorithm that involves local communication among bidders (robots). However, their method focused on ...
Multi-robot task allocation is a crucial issue in a multi-robot system, which concerns the strategy of matching tasks and robots to get higher performance.
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Nov 11, 2024 · The objective of this Systematic Literature Review (SLR) is to provide insights on the recent advancement in Multi Robot Task Allocation(MRTA) problems.