Towards optimal task positioning in multi-robot cells, using nested meta-heuristic swarm algorithms - Mutti, S.; Nicola, G.; Beschi, M.; Pedrocchi, N.; Tosatti, L. Molinari (Robotics and computer-integrated manufacturing, 2021)
While multi-robot cells are being used more often in industry, the problem of work-piece position optimization is still solved using heuristics and the human experience and, in most industrial cases, even a feasible solution takes a considerable amount of trials to be found. Indeed, the optimization of a generic performance index along a path is complex, due to the dimension of the feasible-configuration space. This work faces this challenge by proposing an iterative layered-optimization method that integrates a Whale Optimization and an Ant Colony Optimization algorithm, the method allows the optimization of a user-defined objective function, along a working path, in order to achieve a quasi-optimal, collision free solution in the feasible-configuration space. •Work-piece position affects the outcome of the processing in a robotic operated cell.•Heuristic algorithms are shown to explore consistently the optimization search space.•Task redundancy exploitation is a key factor in robotic operated cells.