Philippine E-Journals

Solving for Uncertainties in Robotic Part Mating and the KALMAN Filter Observability

Alvin Y. Chua | Jayantha Katupitiya | Edwin Calilung

Discipline: Engineering

 

Abstract:

The uncertainty problem present in robotic part-mating situation deals with the identification and compensation of misalignments or errors (uncertainties) that may lead to unsuccessful assembly. Studies have been done employing special equipment throughout the years to try and solve the problem. A novel method of solving for the uncertainties was implemented which used the Kalman Filter with force-moment sensor. A state estimation set-up tested the Kalman Filter implementation. Then, a pre-analysis of the uncertainty identification situation was done to test the effectiveness of the Kalman Filter with force moment sensor strategy. Finally, the observability problem was introduced and solved by using a random contact strategy which decoupled the unobservable uncertainties. The results proved that the Kalman filter with force sensor strategy could solve the grasping and contact uncertainties even in the presence of the observability problem.