Spatial–Temporal Load Balancing and Coordination of Multi-Robot Stations

Abstract

Cycle time minimization in multi-robot manufacturing stations is computationally challenging. This is due to the many aspects that need to be accounted for, including assigning process tasks to robots, specifying robot configurations at tasks, sequencing, planning motions, and coordinating the robots to avoid collisions. Hence, to find good solutions, often some assumptions are made and/or the problem is divided into subproblems-often limiting the set of solutions with the risk of excluding the best ones. In this study, we generalize the completely disjoint solution method that challenges the socalled shortest path assumption, i.e., to let each robot use its shortest collision-free motion between any two configurations, regardless of the other robots. We devise a generalized method called spatial-temporal load balancing and coordination, which prevents robot-robot collisions by a sequence of disjoint solutions, guiding task assignments, sequences, and robot motions (path and velocity). We study both artificial and industrial instances. For some of them, our suggested method is superior to methods based on the shortest path assumption, with as much as a 28% reduction in cycle time. Moreover, for problem instances with no special structure, we establish that the shortest path assumption is often reasonable. Note toPractitioners-This work is motivated by a particular industrial problem instance of a spot-welding station with two robots and where welds are placed along the edge of a workpiece. Due to the special geometry of the instance one robot can only perform welds in the middle of the edge and the other only at the ends. As a result, if the robots use their shortest motions between welds, then waiting times are required to prevent collisions. Moreover, the tasks are too close to each other to allow for a completely disjoint solution. Hence, we suggest a method based on sequence of disjoint solutions.

Automated strategy for tissue analysis in anatomic pathology: fiducial marker integration and multisurface tissue comparison

“…In addition, the successful integration of the platform into the APL workflow will require the creation of dedicated middleware. This middleware should address functional gaps by introducing robotics to facilitate the manipulation of PEFS [33] [34]. It is worth noting that our VMMR platform incorporates a specific step for reading the Data Matrix, which could potentially serve as an interface with additional middlewares.…”