I am responsible for the Robotics Course in the Department of
Computing, attended by third years and MSc students. This is a nine week course which focuses on mobile
robotics, and aims to cover the main issues in this dynamic field via
lectures and a large practical element where students work in groups
and implement robotics ideas using the Lego Mindstorms NXT kits. The
course always finishes with a competition where the groups compete to
build and program the robot which can most effectively achieve a
certain challenge against the clock. See the bottom of this page for pictures and videos
from previous years' competitions.
Jindong Liu is the Course Support Leader for Robotics and another point of contact for questions you might have.
Thank you to Adrien Angeli who was previous CSL on the course and has helped substantially with the preparation of materials and exercises; and to
Ian Harries and
Keith Clark
who developed earlier material from which the current course has evolved.
Lecture and practical sheets for the course will be available from
the links below (the links will come alive gradually throughout term). Extra handouts from the lectures are available further down.
Spring 2012 Lecture Plan
Lectures at 9am on Wednesdays will be held in room 145. In the first week of the course we will stay in the lecture theatre for a combined lecture/tutorial until 12pm.
From the second week of the course onwards, at 10am we will normally head straight down to the lab (room 202) and
spend the 10am-12pm Wednesday slot working on practical tutorial
work. Practical exercises will be set in the lectures and assessed regularly in the labs as explained clearly in the practical sheets. Please check for details each week below and I will annouce any
changes.
The directory RoboticsResources/ contains all the lecture notes, tutorial sheets, additional handouts below and also bits of code that I point to in the practicals.
Here are mirrored electronic versions of extra handouts given out in
paper form during the course (all of these are available elsewhere on
the internet).
Week 1:
Robot Science, Chapter 1, Andrew Davison (A chapter of a popular style book on robotics I am working on... not part of the content of the course but may be an interesting read and any comments welcome).
Berlin Summit on Robotics 2011 Report (Also certainly beyond the scope of this course but this report from a meeting I attended recently gives a good snapshot of the current thinking of various roboticists on the state of the field and current challenges).
This year we had a completely new challenge where the teams had to
build robots able to cross an area filled with obstacles without
bumping into any of them. The robots had to rely on good odometry for
localisation, and then use sonar to detect obstacles and plan a path
between them. Marks were given depending on how far the robots managed to advance, with extra time points for those teams that made it all the way across. The starting point was the techniques for occupancy grid
mapping we had learnt in the course, but the desire for speed meant
that many teams switched to simpler methods due to the high computational cost of occupancy mapping.
The winning robot was developed by Nicolas Paglieri, Clemens Lutz, Antonio Azevedo and Francesco Giovannini and completed the challenge in a remarkably fast 21 seconds, though impressively around half of the teams completed the whole course and a couple came close to this time. The winning team's robot used the Lego light sensors cleverly as proximity sensors, allowing giving the robot an extra obstacle sensor which was particularly useful at high speed, and this together with fast planning gave them the best time.
We used quite a different layout for this year's localisation challenge, with the robots needing to recognise their location and orientation in one of three randomly chosen places and then navigate fast along a long corridor to pre-determined waypoints. Marks were given both for accuracy and time.
The winners' robot was remarkably precise, and its motion included particularly nice curved entries into the waypoint spaces, all while maintaining very good speed such that it beat its nearest competitor by 8 seconds. The members of the winning group were Alexandre Vicente, Ajay Lakshmanan, Garance Bruneau, Kevin Keraudren, Axel Bonnet and Zae Kim (video courtesy of Jindong Liu).
The challenge this year was similar to 2009, but in a new course and with a marking scheme which emphasized accuracy over speed. Again, the robots were placed randomly by me at one of five pre-learned waypoints and had to determine their locations and navigate autonomously to all of the other waypoints --- within 5cm accuracy to gain full marks, which was a challenging problem.
The winning team this time consisted of Jim Li, Daniel Abebe, Robert Kopaczyk, Nicholas Heung and Cheuk Tam, and their robot's successful completion of the course in under 40 seconds is shown below (video courtesy of the team).
Localisation Challenge in 2009
This year's competition challenge required the robots to first
localise from scratch at one of five pre-learned locations, and
then to localise continuously to navigate around a route of
waypoints. The whole process was timed so there was some need to
trade off accuracy for speed in order to win.
Again there were several teams which achieved the challenge
impressively within the target time of 30 seconds, but the
winners by a narrow margin were Ivan Dryanovski, Tingting Li,
Wenbin Li, Edmund Noon and Ke Wang whose winning run is shown in
the video below (video courtesy of the team).
The challenge at the end of the course in 2008 was to implement a
probabilistic localisation algorithm based on particle
filtering, using the Lego Mindstorms NXT kits with motor odometry, sonar and
compass sensors. The groups were given a "map" of a small enclosed
area, indicating the measured locations of walls relative to a
fixed coordinate system. The goal was to use Monte Carlo
Localisation to keep a continuous estimate of the moving robot's
position which was good enough to accurately follow a pre-defined
path through a sequence of waypoints.
Several of the teams achieved good results, and one or two even
made promising progress on the more difficult problem of global
localisation (the "kidnapped robot problem"), where the robot
had to initialise a localisation estimate from scratch when
dropped at an arbitrary position in the course. This video shows the robot of the team of David Passingham, Vincent Dedoyard, John Payce and Mengru Li in action (video courtesy of the team).
Robot Obstacle Course in 2007
At the end of the course in 2007 we had a robot obstacle course challenge
where the students in groups of three or four designed Lego robots to reach
a light beacon while bouncing off and avoiding obstacles. The robots
used light sensors to detect the direction of the bright light and
bump sensors to detect collisions. Each of the robots was timed
over three runs from different start points on a course
constructed by Simon
Overell.
The winning robot was from the team of Philip Stennett, Nicholas Ball,
Maurice Adler and Wei Chieh Soon which completed the course
all three times with a total time of 36.9 seconds --- this is a (very dark) video of their robot in action
. The robots from the team of
Si Yu Li, Henry Arnold, Shobhit Srivastava and Jonathan Dorling, and the team of
Ricky Shrestha, Hussein Elgridly and Maxim Zverev also successfully
completed the course three times.
Robot Racing in 2006
Last year we finished the course with a time-trial competition between
Lego line-following robots designed and programmed by the students
in groups of three. The robots used downward-looking light sensors
to observe the line, and ran programs written in the C-like NQC
language. The robots were timed over three laps of this course, which
the groups saw for the first time on the day of the races:
The easy winner of the time-trial was the simple but very slick robot
from Jiefei Ma,
Winnie Xu Zheng and Nan Wang which you can see in action in
this movie.
Another interesting robot featuring articulation from Steven Lovegrove, Alex Lamaison and
Folabi Ogunkoya performed very well in practice but
didn't quite make it round three laps of the race
track. Also see this movie of several of the robots
on track at once.
(Thanks to Jiefei Ma and Steven Lovegrove for providing the videos).
Andrew Davison
MTS
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