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This course is structured as two parts: (1) articulated robot manipulators and (2) autonomous mobile robotics. Articulated manipulators form an important class of robots that are commonly used in industrial situations. The purpose of this part of the course is to introduce students to fundamental concepts of geometry, kinematics, dynamics, and control of robotic systems allowing students to model and analyse a robot manipulator. The autonomous mobile robotics part of the course is an introduction to the probablistic robotics techniques that underpin self-driving cars and other autonomous robots. This course is project-based and students will be given the opportunity to apply the material in both simulation and with real industrial and research robots through project work.
Develop and apply forward kinematics to obtain the end-effectorposition and orientation in the base coordinate frame as a functionof the joint parameters for an articulated manipulatorApply inverse kinematics to calculate all possible sets ofjoint parameters that result in a given end-effector position andorientation relative to the base coordinate frameConstruct the Jacobian matrix for an articulated manipulator anduse it to calculate static forces and torques and derive dynamicequations for each link Apply simple linear interpolative path planning techniques tocontrol end-effector motion for an articulated manipulatorUnderstand the principles of Bayes filters for probabilistic robotics and their application to sensor fusion, mapping, localisation, and simultaneous localisation and mappingImplement a particle filter and a Kalman filter for robot sensor fusionApply navigation and path planning algorithms to control a robot using the robot operating system (ROS)
Domestic fee $1,038.00
International fee $4,600.00
* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.
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