rsar97/-Adaptive-Filtering-Technique-for-Error-Detection-and-Correction-of-Precision-Welding-RobotAdaptive-
Robotics and Automation have played a major role in the field of automobile manufacturing, space research, logistics, agriculture and many more. One such robot is a welding robot which is programmed to weld a product in the automotive industry. These robots are very accurate and don’t have any errors. But, sometimes due to some vibrations in the motors or due to any external factors, the robot may deviate from its specified position which leads to defective welding of a product. The robot arm is subjected to object tracking. The position of the robot arm is tracked by mounting an accelerometer on the robot arm. This position deviation can be corrected by using Kalman filtering technique. Kalman filters are used in the field of robotics motion planning, control and trajectory optimization. A com-mon application is for state prediction and estimation, object tracking. This paper is about applying Kalman filtering technique to a three-axis accelerometer which is mounted on the robotic arm of a welding robot. The voltage values of the accelerometer sensor are taken for state prediction and by recursive iterations the values are optimized such that error becomes minimum when the robot has deviated from its desired position.