Adaptable Motion Planning Of DELTA Robot For Variable Payload Mass

Delta robot is a parallel manipulator.It is renowned for its speed and also for good accuracy.It is used worldwide in industries to accomplish repetitive tasks with precision and accuracy at high speeds.This makes it one of the most efficient and productive robot.It has an ever-increasing role especially in pick-and-place tasks.Courier and logistic companies in particular are widening its use in package handling.In package-handling,it has to deal with different kinds of payloads which can vary in weight and size.Abundant research is present on the path planning and path tracking of Delta.Most of this research is based on techniques which presume that the mass(and size)of all the payloads is the same.These techniques fail to accommodate the payload mass uncertainty which is a common phenomenon in real life.It is by intuition that we can tell that a motion planning algorithm making computations on the basis of a constant payload mass but practically operating with varying payload masses will run into problems.These problems can range from sub-optimal trajectories to saturation of actuators.Some research is directed towards countering these adverse effects but none has ever quantified these errors.Being a parallel manipulator,Delta has fairly complex kinematics and dynamics.Therefore,the progress towards a more adaptable yet practicable approach has been slow.This thesis aims at measuring the extent to which payload mass uncertainty affects the performance of Delta robot.It will,then,also propose a strategy to counter these effects in a Computed-Torque Control environment.Measurement of the errors introduced by payload mass variation is necessary to verify the hypothesis that it does push the system to sub-optimality.For a robot that is considered one of the world's fastest,this would be a serious detriment.After results from simulations point to the validity of the aforementioned statement,strategies are put forth to mitigate the harmful effects of payload mass uncertainty.Several scenarios simulating the possible real life conditions have been simulated and their results are compared to those of an ideal situation.A remedial motion planning strategy is devised that employs torque feedback from the actuators.It minimizes the error in real time in order to adapt to the payload variation withinpermissible limits and thus avoid saturation of actuators.The results of these simulations are presented using graphs and plots.They are then analyzed to assess the performance of the proposed algorithm in different scenarios.It is revealed through these deliberations that the new algorithm minimizes the errors from payload mass uncertainty and avoids actuator saturation too.