Planning the sequence of components (or parts) to be assembled during manufacturing is an important application problem for virtual environments for three main reasons. First, it is a difficult combinatorial optimization but a highly visual problem. Second, a majority of assembly operations in factories (with the exception of simple pick-and-place operations) are still performed manually, because they are difficult to automate. Hence, it is an important problem involving human-machine interface. Third, there are a number of assembly operations which require dextrous operator training. Hence, it is also an important training problem. Recent research suggests a promising approach for assembly determination based on using heuristic rules to generate soft constraints in addition to the regular hard quantitative constraints due to part geometry and topology. We believe that the emergence of virtual environments can enable us to systematically use these soft constraints, which previously has not been possible. In this paper, we report results of experiments involving fifteen voluntary participants using a nonvirtual reality (VR) environment involving blueprints, a nonimmersive desktop VR environment, and an immersive projection-based VR environment to first teach participants skills in handling soft and hard constraints for assembly planning through examples, and then to measure the effectiveness of their learnt skills in solving a different example problem. We have classified soft constraints as infeasibility constraints, reorientation constraints, difficulty constraints, instability constraints, and dissimilarity constraints. A significant observation is that the participants could, on average, perform the assembly operations in approximately half the time in the immersive and nonimmersive VR environments than in the traditional environment using blueprints.
ASJC Scopus subject areas
- Control and Systems Engineering
- Human-Computer Interaction
- Computer Vision and Pattern Recognition