Vision based patrol robot has been with great interest nowadays due to its consistency, cost effectiveness and no temperament issue. In recent times, Global positioning system (GPS) has been cooperated with Global Navigation Satellite System (GNSS) to come out with better accuracy quality in positioning, navigation, and timing (PNT) services to locate a device. However, such localization service is yet to reach any indoor facility. For an indoor surveillance vision based patrol robot, such limitation hinders its path planning capabilities that allows the patrol robot to seek for the optimum path to reach the appointed destination and return back to its home position. In this paper, a vision based indoor surveillance patrol robot using sensory manipulation technique is presented and an extended Dijkstra algorithm is proposed for the patrol robot path planning. The design of the patrol robot adopted visual type sensor, range sensors and Inertia Measurement Unit (IMU) system to impulsively update the map’s data in line with the patrol robot’s current path and utilize the path planning features to carry out obstacle avoidance and re-routing process in accordance to the obstacle’s type met by the patrol robot. The result conveyed by such approach certainly managed to complete multiple cycles of testing with positive result.
A modified Q-learning algorithm for robot path planning in a digital twin assembly system