{"ID":2827105,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.17584","arxiv_id":"2512.17584","title":"Optimized Scheduling and Positioning of Mobile Manipulators in Collaborative Applications","abstract":"The growing integration of mobile robots in shared workspaces requires efficient path planning and coordination between the agents, accounting for safety and productivity. In this work, we propose a digital model-based optimization framework for mobile manipulators in human-robot collaborative environments, in order to determine the sequence of robot base poses and the task scheduling for the robot. The complete problem is treated as black-box, and Particle Swarm Optimization (PSO) is employed to balance conflicting Key-Performance Indicators (KPIs). We demonstrate improvements in cycle time, task sequencing, and adaptation to human presence in a collaborative box-packing scenario.","short_abstract":"The growing integration of mobile robots in shared workspaces requires efficient path planning and coordination between the agents, accounting for safety and productivity. In this work, we propose a digital model-based optimization framework for mobile manipulators in human-robot collaborative environments, in order to...","url_abs":"https://arxiv.org/abs/2512.17584","url_pdf":"https://arxiv.org/pdf/2512.17584v1","authors":"[\"Christian Cella\",\"Sole Ester Sonnino\",\"Marco Faroni\",\"Andrea Zanchettin\",\"Paolo Rocco\"]","published":"2025-12-19T13:50:07Z","proceeding":"cs.RO","tasks":"[\"cs.RO\"]","methods":"[]","has_code":false}