Multi-robot spot-welding cell design: Problem formalization and proposed architecture

The multi-robot cell design for car-body spot welding is faced by industry as a sequence of tasks, where researches are focused on issues of the problem as a whole. In authors’ knowledge, none work in literature have suggested any formalization for the complete process. This paper tries to bridges the gap proposing coherent process formalization, and presenting a corresponding innovative architecture for the automatic optimal cell design. Specifically, the formalization involves the identification and allocation of the resources in terms of a set of decisional variables (e.g. robot model/positioning/number, welding gun models/allocation/number, welding point allocation etc.); then, the design optimization process minimizes the investment costs granting the cycle time. The multi-loop optimization architecture integrates both new algorithms and existent procedures from different fields. Test-bed showing its feasibility is reported

Multi-robot spot-welding cells: An integrated approach to cell design and motion planning

The necessity to manage several vehicle models on the same robotized assembly cell has made the cell design and the robot off-line motion planning two fundamental activities. Industrial practice and state-of-the-art methods focus on the technical issues of each activity, but no integrated approach has been yet proposed, resulting in a lack of optimality for the final cell configuration. The paper introduces a formalization of the whole process and proposes a heuristic multi-stage method for the identification of the optimal combination of cell design choices and motion planning. The proposed architecture is depicted through a real case for welding application

Validation of an extended approach to multi-robot cell design and motion planning

According to both industrial practice and literature, multi-robot cell design and robot motion planning for vehicle spot welding are two sequential activities, managed by different functional units through different software tools. Due to this sequential computation, the whole process suffers from inherent inefficiency. In this work, a new methodology is proposed, that overcomes the above inefficiency through the simultaneous resolution of design and motion planning problems. Specifically, three mathematical models were introduced that (i) select and positions the resources, (ii) allocate the tasks to the resources and (iii) identify a coordinated robot motion plan. Based on the proposed methodology, we built three ad-hoc cases with the goal to highlight the relations between design, motion planning and environment complexity. These cases could be taken as reference cases so on. Moreover, results on an industrial case are presented

Efficient Industrial Solution for Robotic Task Sequencing Problem With Mutual Collision Avoidance & Cycle Time Optimization

© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksIn the automotive industry, several robots are required to simultaneously carry out welding sequences on the same vehicle. Coordinating and assigning welding points between robots is a manual and difficult phase that needs to be optimized using automatic tools. The cycle time of the cell strongly depends on different robotic factors such as the task allocation among the robots, the configuration solutions and obstacle avoidance. Moreover, a key aspect, often neglected in the state of the art, is to define a strategy to solve the robotic task sequencing with an effective robot-robot collision avoidance integration. In this paper, we present an efficient iterative algorithm that generates a high-quality solution for Multi-Robotic Task Sequencing Problem. This latter manages not only the mentioned robotic factors but also aspects related to accessibility constraints and mutual collision avoidance. In addition, a home-developed planner ( RoboTSPlanner ) handling 6 axis has been validated in a real case scenario. In order to ensure the completeness of the proposed methodology, we perform an optimization in the task, configuration and coordination space in a synergistic way. Comparing to the existing approaches, both simulation and real experiments reveal positive results in terms of cycle time and show the ability of this method to be interfaced with both industrial simulation software and ROS-I tools.Peer ReviewedPostprint (published version