It is important for a robot to acquire adaptive behaviors for avoiding surrounding robots and obstacles in complicated environments. Although the introduction of a learning scheme is expected to be one of the solutions for this purpose, a large size of memory and a large calculation cost are require
Case learning for CBR-based collision avoidance systems
β Scribed by Yuhong Liu; Chunsheng Yang; Yubin Yang; Fuhua Lin; Xuanmin Du; Takayuki Ito
- Publisher
- Springer US
- Year
- 2010
- Tongue
- English
- Weight
- 761 KB
- Volume
- 36
- Category
- Article
- ISSN
- 0924-669X
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