Task allocation and scheduling in collaborative robotics

• Autor(a) principal: Pereira, Joana Filipa Vieira Santos
• Data de Publicação: 2022
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10773/37844
• topic: Task scheduling; Task allocation; Collaborative robotics; Cobot; Systematic literature review; Taxonomy; Task assignment and scheduling algorithm; GRASP; Greedy Randomized Adaptive Search Procedure

The current technological challenges that industries face, are characteristic of the Fourth Industrial Revolution or, also called, Industry 4.0 (I4.0) and to overcome them, industries must have flexibility and a greater focus on the human being in their processes. One of the brand-new technologies that I4.0 brings are the collaborative robots. Therefore, in order to face the challenge of increasing productivity together with increasing flexibility, collaborative robots or cobots can represent a greater help for production systems to overcome these challenges. In fact, when compared to traditional industrial robots, cobots are lighter, occupy less shop-floor space, can interact with the human worker and are easier to change their location, bringing versatility and adaptability that allows companies to adapt their processes more easily to the unstable demand patterns. As a result of the implementation of collaborative robotics on the factory floor, cobots will share the workspace and tasks with human workers and, thus, it is essential to assign and schedule tasks between humans and robots for an efficient and effective collaboration, considering the strengths and limitations of each agent. It is in this context that the present dissertation is inserted, having as main objective the exhaustive study of the allocation and scheduling of tasks in collaborative robotics. Therefore, a systematic review of the literature is presented, respective quantitative and qualitative analyses, a taxonomy is elaborated, processes of three industries are mapped in BPMN 2.0. Finally, the development of an algorithm to solve the problem of allocation and scheduling tasks between a robot and a human through tan algorithm inspired in the GRASP (Greedy Randomized Adaptive Search Procedure) metaheuristic, minimizing the total time and the ergonomic risk for workers.