Perturbation Observer-Based Obstacle Detection and Its Avoidance Using Artificial Potential Field in the Unstructured Environment

Different methodologies for manipulators have been proposed and applied to robot obstacle detection avoidance in unstructured environments. These methods include different real-time sensors, observer-based algorithms, path planning using genetic algorithms. However, sensor design integration is complex considerably expensive. Moreover, the observer algorithm requires complete system dynamics information, which difficult derive. In this regard, algorithms are typically considered slow optimize. Accordingly, study proposes a sensor-less technique nonlinear (known as sliding perturbation (SPO)). Obstacle also implemented motion planner artificial potential field (APF)). The SPO that only partial position provides all other states (such position, velocity) (non-linearities external disturbance). estimates torque at each joint resulting from contact (i.e., collision) with an obstacle. Obstacles detected avoided by integrating APF. estimated detects location repulsive force APF avoid To achieve avoidance, sum of torques must be zero. manipulator five degrees freedom.