ENMT482-24S2 (C) Semester Two 2024

Robotics

15 points

Details:
Start Date: Monday, 15 July 2024
End Date: Sunday, 10 November 2024
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Sunday, 28 July 2024
  • Without academic penalty (including no fee refund): Sunday, 29 September 2024

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 2024

Students must attend one activity from each section.

Lecture A
Activity Day Time Location Weeks
01 Monday 13:00 - 14:00 E5 Lecture Theatre
15 Jul - 25 Aug
9 Sep - 20 Oct
Lecture B
Activity Day Time Location Weeks
01 Wednesday 11:00 - 12:00 E9 Lecture Theatre
15 Jul - 25 Aug
9 Sep - 20 Oct
Lecture C
Activity Day Time Location Weeks
01 Thursday 10:00 - 11:00 E5 Lecture Theatre
15 Jul - 25 Aug
9 Sep - 20 Oct
Lab A
Activity Day Time Location Weeks
01 Tuesday 13:00 - 15:00 Elec 109 Automation Lab
15 Jul - 21 Jul
02 Wednesday 12:00 - 14:00 Elec 109 Automation Lab
15 Jul - 21 Jul
03 Tuesday 13:00 - 15:00 Elec 109 Automation Lab
22 Jul - 28 Jul
04 Monday 14:00 - 16:00 Elec 109 Automation Lab
22 Jul - 28 Jul
05 Tuesday 13:00 - 15:00 Elec 109 Automation Lab
29 Jul - 4 Aug
06 Monday 14:00 - 16:00 Elec 109 Automation Lab
29 Jul - 4 Aug
07 Tuesday 13:00 - 15:00 Elec 109 Automation Lab
5 Aug - 11 Aug
08 Monday 14:00 - 16:00 Elec 109 Automation Lab
5 Aug - 11 Aug
09 Tuesday 13:00 - 15:00 Elec 109 Automation Lab
12 Aug - 18 Aug
10 Monday 14:00 - 16:00 Elec 109 Automation Lab
12 Aug - 18 Aug
11 Tuesday 13:00 - 15:00 Elec 109 Automation Lab
19 Aug - 25 Aug
Lab B
Activity Day Time Location Weeks
01 Thursday 11:00 - 13:00 Mech 214 Mechatronics Lab (12/9-17/10)
Mech 113 Robotics Lab (12/9-17/10)
9 Sep - 20 Oct

Course Coordinator / Lecturer

Michael Hayes

Lecturer

Chris Pretty

Indicative Fees

Domestic fee $1,197.00

International fee $6,000.00

* 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

  • ENMT482-24S2 (C) Semester Two 2024