Optimum Utilization Of Energy Consumption In Arm Robot

This paper introduced on how to minimize the energy and performance of arm robot. The objective is to design the optima; performance of the arm robot movement in performing certain tasks. There are three process involved in minimize the energy which are hardware assembly selection, Denavit Haternberg (D-H) parameters and optimization process of robot movements. A 3 degree of freedom ROB0036 robot arm is use as hardware selection. Then determine the Denavit Haternberg (D-H) parameters for robot through theoretical, simulation and practical forward and inverse kinematics. The optimization process involved how to control parameters know as position angle and the speed of motor of three main axes of arm robot. The performance is measured respect to the two movement, which are reference and optimized. The energy efficiency analysis is performs to reduce this energy consumed. The simulation resulted show that the minimum motor’s movement of joint, the less time taken to achieve of to complete the pick and place task. Directly, it results on less energy used and increase the robot arm performance

Minimum Jerk Trajectory Planning for Trajectory Constrained Redundant Robots

In this dissertation, we develop an efficient method of generating minimal jerk trajectories for redundant robots in trajectory following problems. We show that high jerk is a local phenomenon, and therefore focus on optimizing regions of high jerk that occur when using traditional trajectory generation methods. The optimal trajectory is shown to be located on the foliation of self-motion manifolds, and this property is exploited to express the problem as a minimal dimension Bolza optimal control problem. A numerical algorithm based on ideas from pseudo-spectral optimization methods is proposed and applied to two example planar robot structures with two redundant degrees of freedom. When compared with existing trajectory generation methods, the proposed algorithm reduces the integral jerk of the examples by 75% and 13%. Peak jerk is reduced by 98% and 33%. Finally a real time controller is proposed to accurately track the planned trajectory given real-time measurements of the tool-tip\u27s following error