Project Areas and Indicative Projects
Projects will be divided into 3 broad areas. Within each area, an
indication of possible projects (to be finalised) is given below.
Applicants should rank their preferences in terms of project areas.
PROJECT AREA: SENSOR PROCESSING & INFERENCE (SPI)
A critical part of all robotics applications is the ability to process
sensor data and infer important information about the environment from
the data. In the RoboCup Soccer, Standard Platform League application,
the primary sensor available is the robot's camera (single colour
camera with resolution up to 640x480). In addition, the robot includes
inertial sensors (accelerometers and gyroscopes) and foot pressure
sensors. This application motivates a number of projects in semsor
processing and inference. Indicative projects (to be finalised) include:
- Implementation of Automatic Robot Location Algorithms
- Real-Time Stereo Vision Based Localisation and Object Recognition
- Obstacle detection using the GOLD paradigm
- Fast accurate robust ball tracker
- Single Camera Object Detection & Tracking for Robot Soccer
- Line feature detection algorithm development from webcam images
PROJECT AREA: BALANCE CONTROL & ACTION (BCA)
Another core autonomous robotics skill involves actuation. In the case
of wheeled robots, this is relatively straightforward where geared
motors may be controlled to give desired motions. In the case of legged
robots, particularly humanoid types, there is much work required to
plan the correct sequence of joint movements to create a 'good' walk,
to be able to kick the ball, and to be able to balance when disturbed
(for example by accidental collisions with other objects). Example
projects in this area include:
- Balancing a planar robot using arm motion.
- Robot tilt stabilization based on foot pressure feedback
- Robot kick design
- Goal keeper saves
PROJECT AREA: LEARNING, PLANNING & COORDINATION (LPC)
To make the best use of the sensor information and the available
actuators, intelligent, strategic decision making is required. This
allows the robots to cooperate as a team, to make best advantage of
their possible actions, to give the team the best chance of both
avoiding opponent goals, and scoring their own goals. Possible projects
in this area include:
- Capture & Analysis of Opposition Data to Improve Game
Performance
- Irregular Cellular Automata for Robot Motion Planning
- Multi-criteria path planning & decision-making for
co-operating robots
- Specification and Simulation of Soccer Tactics.
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