A constraint-based motion control strategy for cantilever snap assemblies

Industrial snap assembly processes remain largely a manual task. Much of the research in snap assembly has not sought to design strategies and controllers according to the class of snap-fastener used. Three fastener types are used in manufacturing: cantilever, torsional, and annular snaps. As a first step in solving the snap automation problem, sought to devise a force control strategy that could effectively perform cantilever-snap assemblies for various degrees of complexity and one that could generate reproducible sensory-motor signals across trials as a basis to facilitate the future discrimination of force signals and enable a robot to reason about the assembly's task state. Our contribution is two-fold, a control strategy that: (i) exploits constraint-motion designs built into cantilever snap parts to more effectively complete the task, and (ii) a strategy that can be applied to cantilever-snap parts of growing varying complexity such as those containing, one, two, or four snaps. The control basis approach was used as a framework to design force controllers for the Pivot Approach. The framework's modularity and scalability enables the flexible adaptation of force controllers to snaps of varying complexities and geometries. The Pivot Approach simulation results showed that the control strategy took advantage of hardware designs increasing the likelihood of successful insertions and yielding consistent sensory-motor signal patters across trials for the snap assembly. These results serve as foundational work to devise new signal interpretation methods to enable robot to reason about the assembly state and produce more fault tolerant behaviors.