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» Mobile robot learning by evolution of fuzzy controller
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IROS
2007
IEEE
179views Robotics» more  IROS 2007»
14 years 1 months ago
Incremental learning for place recognition in dynamic environments
Abstract— Vision-based place recognition is a desirable feature for an autonomous mobile system. In order to work in realistic scenarios, visual recognition algorithms should be ...
Jie Luo, Andrzej Pronobis, Barbara Caputo, Patric ...
RAS
2008
80views more  RAS 2008»
13 years 7 months ago
Motion design and learning of autonomous robots based on primitives and heuristic cost-to-go
The task of trajectory design of autonomous vehicles is typically two-fold. First, it needs to take into account the intrinsic dynamics of the vehicle, which are sometimes termed ...
Keyong Li, Raffaello D'Andrea
SMC
2010
IEEE
132views Control Systems» more  SMC 2010»
13 years 6 months ago
Selection of SIFT feature points for scene description in robot vision
This paper presents a method for selection of SIFT(Scale-Invariant Feature Transform) feature points using OC-SVM (One Class-Support Vector Machines). We proposed the method for au...
Yuya Utsumi, Masahiro Tsukada, Hirokazu Madokoro, ...
IJCAI
2007
13 years 9 months ago
Online Speed Adaptation Using Supervised Learning for High-Speed, Off-Road Autonomous Driving
The mobile robotics community has traditionally addressed motion planning and navigation in terms of steering decisions. However, selecting the best speed is also important – be...
David Stavens, Gabriel Hoffmann, Sebastian Thrun
GECCO
2009
Springer
14 years 5 days ago
NEAT in increasingly non-linear control situations
Evolution of neural networks, as implemented in NEAT, has proven itself successful on a variety of low-level control problems such as pole balancing and vehicle control. Nonethele...
Matthias J. Linhardt, Martin V. Butz