Demonstrating Cognition by Task Execution and Motion Planning with different algorithms for Manipulation

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2018

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Abstract

In this Thesis we demonstrate the whole path until the manipulation and the planning of the Baxter Robot. We start by analyzing the kinematic analysis of a six degrees of freedom robot. We build our analysis starting from the Denavit-Hartenberg method. We proceed with the kinematic equations of the robot and with the inverse kinematics as well as with a kinematic simulation of its movement with matlab. In order to reach our final goal we continue with the kinematic and dynamic analysis of the Baxter robot. We again state the Denavit-Hartenberg matrix, but this time we continue by building the dynamic model of the Baxter robot through the Euler-Lagrange equations. Moving on, we explore planning algorithms. The knowledge of which will help us in order to finally be able to formulate our path planner for the Baxter robot. We experiment ourselves by implementing four planning algorithms in different path planning problems. We construct the RRT and the RRT* algorithms in Python and we process them in different planning problems. Moving on, we also implement a planning problem in which Q-Learning and Sarsa algorithms are being used. We demonstrate how those two planning and learning algorithms work in our specified problem and we compare our results. Having knowledge on dynamic and kinematic robotic analysis and planning and motion planning algorithms we then experiment ourselves with the Baxter simulator on Gazebo. Also we plan the Baxter robot with Moveit!, getting familiar with the use of ROS as well as with the software. We add obstacles in our world and we plan our Baxter robot measuring its speed. We finally build a different plan algorithm RRT+ by focusing on searching for a secure and realizable path plan starting from the lower dimension space and then adding degrees of freedom to our Baxter robot. Concluding, we have built the desired steps for someone in order to build up the required knowledge to deal with robots and artificial intelligence planning.

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