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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2031/471
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| Title: | Project AIBO - machine learning and object recognition |
| Authors: | Shum, Tsz Kin |
| Department: | Department of Computer Science |
| Issue Date: | 2004 |
| Supervisor: | Prof. Ip Horace H S. First Reader: Wong Hau San. Second Reader: Chun H W Andy |
| Abstract: | AIBO in Japanese means “companion”. It is also an acronym for Artificial Intelligence
Robot. AIBO expresses real emotions and instincts. Explore the world of AIBO and
discover a friendship that matures with time.
AIBO is a robotic dog developed by SONY, it contained various sensor including
touch sensor, temperature sensor, camera, distance and sound sensor, mic and
LEDs. With support of RISC CPU and real-time OS, AIBO can be programmed to be
have intelligent and do different kind of motion as well as tasks.
AIBO provided us a chance to explore topics on AI, multi-agent system, computer
vision, sound recognition, strategy acquisition, real-time reasoning and more.
Recently, robocup is being held and use AIBO to play football match. It is a task for a
team of multiple fast-moving robots under a dynamic environment. Its ultimate goal is
to develop a fully autonomous humanoid robots that can win against the human world
champion team in soccer.
It is not difficult to imagine that robots will soon enter our life and help us to finish
some daily tasks. We will work close together will robot in the future, just like the
scenes in the movie A.I.
As robot will become more and more important to human life, it is worth to do
research on various topics about robotics. In this report, we define computer vision as
the main topic. The technique to achieve computer vision and the methods on object
recognition will be discussed. We may put some emphasis on the robotic vision since
we will use AIBO to recognize some objects in a specified environment. Two
approaches are discussed and tested to proof their feasibility on shape recognition.
With support of experiment results, the second approach, using shape area and
perimeter to area ratio is used and have implemented on AIBO. This approach can successfully
identify some colored objects but not all. The reasons behind will be
discussed. For more, difficulties on robotic vision recognition will also be investigated. |
| Appears in Collections: | Computer Science - Undergraduate Final Year Projects
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