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Intelligent Autonomous Robotics Practicals

Semester 1 2012/2013

Lecturer: Barbara Webb

This page describes the assignments and deadlines for the IAR course. More information, such as how to use the robots, answers to questions arising etc. can be found at the IAR practicals wiki

Demonstrator: Your first contact for problems with the practicals is Alex Davies.

Summary of deadlines *NOTE* change to final deadlines

Week 3	Task 1: Robot avoids obstacles and follows walls.	First report due Thursday 4th October	Demo due at practical week 3
Week 5	Task 2: Robot can combine behaviours.	Report due Thursday 18th October	Demo due at practical week 5
Week 8	Task 3: Robot collects maximum food in minimum time.	Final Report due Wednesday 14th November	Final competition at practical week 9

You should submit just one joint report per group. If there is any reason you do not think the marks for the report should be distributed evenly amongst the group members, please put a note on the report stating what percentage split you have agreed. Please also make sure that the front page of your report has your names and student numbers on it.

Submission should be an electronic document in pdf format, submitted via the on-line submit system by 4pm:

submit iar 1 Your_surnames_report1.pdf

(For later reports replace "1" with 2 or 3 as appropriate)

Note that the first two tasks are assessed, but worth only a small number of marks (2% for the demo, 3% for the report), as their purpose to make sure you are making steady progress at the start of semester, and to give you feedback as you go on how to write a good report. You should consider them as `practice runs' for the final report, worth 40% of your final grade.

Guidance on report writing.

Task 1

First, your robot should move around without hitting obstacles or getting stuck in corners or dead-ends. Second, it should tend to follow long walls, keeping a consistent distance away from the wall, but it should not track round and round small obstacles.

In implementing this task you should particularly explore different ways of using the eight IR sensors: for example, reactively using one pair of IR for avoiding obstacles and another pair for wall following; or combining all the readings to try to identify the shape around the robot before deciding how to act. You should also explore whether particular ways of moving are more or less effective: for example on-the-spot turns vs. curved paths. In your report you could discuss whether you think a change in the physical design of the robot could have made the task easier.

If you have time, you should also implement basic odometry on your robot (see IVR practical 5) so that you can re-draw the tracks that the robot followed during your tests. If you feel really ambitious, you could try to use this to build a basic map of the arena by having the robot record, along with its current position, what walls or obstacles were detected around it in that position, and redrawing these as well.

Demonstration (2 marks) due at practical week 3.

Report (3 marks) on Thursday week 3 (4th October) at 4pm.

Submission should be an electronic document in pdf format, submitted via the on-line submit system by 4pm:

submit iar 1 Your_surnames_report1.pdf

Marked reports will be returned at the practical in week 4.

Task 2

The aim of this task is for your robot to combine several behaviours. As before, the robot should not get stuck (note, this might require more than one `basic behaviour', e.g. to deal with different kinds of obstacles), but at the same time it should move as quickly as it can towards a bright light source (a lamp). The lamp may change position while the robot is moving, and obstacles may be suddenly added or removed from arena. You can use any of the methods for combining behaviours discussed in the lectures, or devise your own method, but should explain and evaluate your choice in the report.

Demonstration (2 marks) due at practical week 5.

Report (3 marks) on Thursday week 5 (17th October) at 4pm.

Submission should be an electronic document in pdf format, submitted via the on-line submit system by 4pm:

submit iar 2 Your_surnames_report2.pdf

Marked reports will be returned at the practical in week 6.

Task 3

This task is inspired by ant navigation capabilities, but you can use any algorithm you like to solve it (i.e. it does not have to be a bio-inspired algorithm).

The robot will start from a particular location, the 'nest' (marked by small cross on floor). There will be a light source on one side of the arena (the 'sun'). The robot needs to explore the arena looking for 'food' (small circles on the floor). Finding food will be signalled to the robot by dropping a cardboard ring around the robot so that gets high readings on all proximity sensors, low on all light sensors. The robot should stop when this happens to indicate that it has 'picked up' the food item. That food location will now be considered empty until the robot has visited the nest location.

To gain points, the robot has to deposit as much 'food' as possible at the nest within 5 minutes. Food is deposited by the robot returning to the nest location and indicating it is dropping off food by doing a 360 degree rotation on the spot (we will allow getting back to within 10cm radius of the location to count as success).

You can decide whether you want the robot to go home everytime it picks up food; whether it should keep going back to the same place to get more, or should explore for new sources; or if it should try to collect multiple food items from different places before going home.

The layout of the arena (walls and obstacles) will be fixed and you can programme the robot with a map if you want. However, food locations will not be known in advance.

Competition at practical week 9.

Final Report (40 marks) on Wednesday week 9 (14th November) at 4pm.

Submission should be an electronic document in pdf format, submitted via the on-line submit system by 4pm:

submit iar 3 Your_surnames_report3.pdf

Marked reports will be returned via the ITO by week 10.

Last update: September 14, 2012.