ENMT482-23S2 (C) Semester Two 2023

Robotics

15 points

Details:
Start Date: Monday, 17 July 2023
End Date: Sunday, 12 November 2023
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Sunday, 30 July 2023
  • Without academic penalty (including no fee refund): Sunday, 1 October 2023

Description

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.

Learning Outcomes

1. Develop and apply forward kinematics to obtain the end-effector position and orientation in the base coordinate frame as a function of the joint parameters for an articulated manipulator

2. Apply inverse kinematics to calculate all possible sets of joint parameters that result in a given end-effector position and orientation relative to the base coordinate frame

3. Construct the Jacobian matrix for an articulated manipulator and use it to calculate static forces and torques and derive dynamic equations for each link
   
4. Apply simple linear interpolative path planning techniques to control end-effector motion for an articulated manipulator

5. Understand the principles of Bayes filters for probabilistic robotics and their application to sensor fusion, mapping, localisation, and simultaneous localisation and mapping

6. Implement a particle filter and a Kalman filter for robot sensor fusion

7. Apply navigation and path planning algorithms to control a robot using the robot operating system (ROS)

Prerequisites

Timetable 2023

Students must attend one activity from each section.

Lecture A
Activity Day Time Location Weeks
01 Monday 12:00 - 13:00 E9 Lecture Theatre
17 Jul - 27 Aug
11 Sep - 22 Oct
Lecture B
Activity Day Time Location Weeks
01 Tuesday 13:00 - 14:00 E9 Lecture Theatre
17 Jul - 27 Aug
11 Sep - 22 Oct
Lecture C
Activity Day Time Location Weeks
01 Wednesday 13:00 - 14:00 E9 Lecture Theatre (19/7-23/8)
E5 Lecture Theatre (13/9-18/10)
17 Jul - 27 Aug
11 Sep - 22 Oct
Lab A
Activity Day Time Location Weeks
01 Thursday 14:00 - 16:00 Elec 109 Automation Lab
17 Jul - 23 Jul
02 Thursday 11:00 - 13:00 Elec 109 Automation Lab
17 Jul - 23 Jul
03 Thursday 12:00 - 14:00 Elec 109 Automation Lab
24 Jul - 30 Jul
04 Thursday 14:00 - 16:00 Elec 109 Automation Lab
24 Jul - 30 Jul
05 Thursday 11:00 - 13:00 Elec 109 Automation Lab
31 Jul - 6 Aug
06 Thursday 14:00 - 16:00 Elec 109 Automation Lab
31 Jul - 6 Aug
07 Thursday 14:00 - 16:00 Elec 109 Automation Lab
7 Aug - 13 Aug
08 Thursday 11:00 - 13:00 Elec 109 Automation Lab
7 Aug - 13 Aug
09 Thursday 11:00 - 13:00 Elec 109 Automation Lab
14 Aug - 20 Aug
10 Thursday 14:00 - 16:00 Elec 109 Automation Lab
14 Aug - 20 Aug
11 Thursday 14:00 - 16:00 Elec 109 Automation Lab
21 Aug - 27 Aug
Lab B
Activity Day Time Location Weeks
01 Thursday 12:00 - 14:00 Mech 214 Mechatronics Lab
11 Sep - 22 Oct

Course Coordinator

Michael Hayes

Lecturer

Chris Pretty

Indicative Fees

Domestic fee $1,164.00

International fee $5,750.00

* 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.

For further information see Mechanical Engineering .

All ENMT482 Occurrences

  • ENMT482-23S2 (C) Semester Two 2023