Design of a Modular Gripper Family Using Solution Spaces

Robotic grippers are often designed as custom solutions to meet specific handling requirements, resulting in a large number of component variants and high lifecy- cle costs. Optimizing grippers for individual use cases will maximize performance. When they share components, cost may be reduced, however, performance may be compromised. This work aims at minimizing the number of components while maintaining a minimum performance. Co-designing grippers that share components across multiple use cases is an expensive combinatorial optimization problem. Unlike conventional optimisation approaches that yield point-based solutions, the proposed method here identifies the intersection of permissible design variables—so-called solution spaces— to define a compact, standardised set of interchangeable modules. This way, gripper families can be identified at significantly reduced numerical cost. The approach is applied to grippers intended for 6 different cylindrical objects of varying mass, geometry, stiffness and friction coefficient. The number of component variants could be reduced from 21 for individual grippers to 9 for the resulting gripper family.