In aerospace, automated assembly line, and precision engineering, asymmetric multi-robot systems comprising serial and parallel robots leverage the complementary strengths of these configurations to address the conflicting demands of high load capacity, extensive range, and flexibility in assembly tasks. However, the relatively small workspace of the parallel robot limits the full potential of the collaborative system functionality. This paper centers on a collaborative assembly system involving serial-parallel robots, whose collaborative workspace is determined by using a combination of the Monte Carlo method and lattice method. Additionally, a multi-objective optimization model is developed to holistically evaluate the collaborative workspace performance. The optimization problem is solved by an enhanced NSGA-II algorithm, which yields a Pareto optimal solution set. This result offers valuable technical insights for designing collaborative systems tailored to diverse task requirements.
