Tolerance dataset: mating process of plug-in cable connectors for wire harness assembly tasks

In this research, we studied the mating tolerance of various plug-in cable connectors and provide a mating tolerance dataset of 70 different connectors. This dataset will be highly advantageous to industries for wire harness assembly tasks using robots. Understanding the mating tolerance is crucial for automating the mating process because it is closely related to the control specifications of a robotic manipulator. Our system uses a 2-finger Robotiq adaptive gripper attached to a 6 degree-of-freedom industrial robot (ABB Robotics) to test the mating process of wire harness assembly tasks. In addition, we use 70 types of wire harness connectors with different numbers of pins widths, lengths, and thicknesses, and various shapes, to test the mating tolerance. The results indicate that the connector mating tolerance of our dataset is more generous than the repeatability of conventional industrial manipulators, and further demonstrate the suitability of the position control methods to wire harness assembly tasks.

     

Combined task and motion planning system for the service robot using hierarchical action decomposition

Intelligent Service Robotics - A service robot needs integration of symbolic reasoning for high-level task planning and geometric computation for low-level motion planning to provide services in an...     

Optimal Power Flow Subject to Security Constraints Solved With a Particle Swarm Optimizer

This paper presents a novel approach to solve an optimal power flow problem with embedded security constraints (OPF-SC), represented by a mixture of continuous and discrete control variables, where the major aim is to minimize the total operating cost, taking into account both operating security constraints and system capacity requirements. The particle swarm optimization (PSO) algorithm with reconstruction operators (PSO-RO) has been used as the optimization tool. Such operators guarantee searching the optimal solution within the feasible space, reducing the computation time and improving the quality of the solution. Results on systems from the specialized literature are adopted to validate the proposed approach.