Acceptance sampling is used to decide either the whole lot will be accepted or rejected, based on inspection of randomly sampled items from same lot. As an alternative traditional plans, it possible use Bayesian approaches using previous knowledge process variation. This study presents a two-sided group chain plan (BTSGChSP) by various combinations design parameters. In BTSGChSP, preceding as w...

Motion planning for spatially constrained robots is difficult due to additional constraints placed on the robot, such as closure constraints for closed chains or requirements on end-effector placement for articulated linkages. It is usually computationally too expensive to apply sampling-based planners to these problems since it is difficult to generate valid configurations. We overcome this ch...

Asymptotically-optimal motion planners such as RRT* have been shown to incrementally approximate the shortest path between start and goal states. Once an initial solution is found, their performance can be dramatically improved by restricting subsequent samples to regions of the state space that can potentially improve the current solution. When the motion planning problem lies in a Euclidean s...