Autonomous Robotic Arm with an Intelligent Gripper

This MSc research project focuses on the modelling, design and implementation of an autonomous robotic arm platform with an intelligent gripper based on a Scorbot ER-4u robotic platform. The gripper employs force feedback control to enable the handling of objects without dropping or crushing. Matlab is used to control the robot arm. Various object recognition algorithms have been developed and compared for an object sorting task. Fig. 1 below summarises the key components of the robotic arm control system.

Fig. 1: Overview of robotic arm control system in Matlab

More details about the algorithms developed for object recognition, inverse kinematic models, and force feedback control are available in the files below.

For more details on this project refer to the following:

Journal Paper:

1. Kumar, R., Mehta, U. and Chand, P. A Low Cost Linear Force Feedback Control System for a Two-Fingered Parallel Configuration Gripper. Procedia Computer Science, 2017, 105(1), 264-269.

Conference Proceedings Paper:

1. Kumar, R. and Chand, P. Inverse Kinematics Solution for Trajectory Tracking using Artificial Neural Networks for SCORBOT ER-4u. The 6^th International Conference on Automation, Robotics and Applications, 2015, pp. 364-369, Queenstown, New Zealand.

2. Kumar, R., Kumar, S., Lal, S. and Chand, P. Object Detection and Recognition for a Pick and Place Robot. In Proceedings of IEEE Asia-Pacific World Congress on Computer Science and Engineering, 2014, Nadi, Fiji.