J.A. Meyer. Evolutionary approaches to neural control in mobile robots. In IEEE Int. Conference on Systems, Man and Cybernetics, 1998. Home/Search Document Details and Download
Summary Related Articles Check |
This paper is cited in the following contexts:
Conducting Evolutionary Robotic Experiments, Proceedings of the.. - And (2002) (Correct)
.... off the shelf components; they are a plug and play robot colony that is used for task planning and control. Further, an EvBot can be used individually, e.g. in a security or search and rescue application. A review of the literature shows that evolutionary robotics is an active research area [5]. Early research was limited to simple sensor motor control. Currently, more hierarchically ordered architectures are being suggested and there is discussion on whether knowledge based algorithms are more efficient than evolutionary algorithms [5] There is also discussion with regard to the ....
....evolutionary robotics is an active research area [5] Early research was limited to simple sensor motor control. Currently, more hierarchically ordered architectures are being suggested and there is discussion on whether knowledge based algorithms are more efficient than evolutionary algorithms [5]. There is also discussion with regard to the scalability issues [2] Worldwide, many groups have developed miniature mobile robot platforms. Some have been designed and built from discrete components [1] 2] 4] others [6] have been adapted from other systems. Whereas the adapted systems leave ....
Meyer, J-A., "Evolutionary Approaches to Neural Control in Mobile Robots", In: Proceedings of the 1998.
Evolving Modular Neural Networks - To Solve Challenging (2003) Self-citation (Meyer) (Correct)
No context found.
J.-A. Meyer. Evolutionary approaches to neural control in mobile robots. In Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, San Diego, 1998.
Evolving Neural Networks - For The Control (1990) (1 citation) Self-citation (Meyer) (Correct)
....e cient than a hand designed PID based controller that independently controlled the blimp s three degrees of freedom. Keywords: neural networks, evolution, lenticular blimp 1 Introduction Over about the past ten years, attempts at evolving neural controllers for robots have proliferated (see [4] for a review) and this approach is currently the most popular in evolutionary robotics ( 6, 5] However, it mostly involves crawling, rolling or walking robots, i.e. robots that move on the ground, and much more rarely swimming or ying robots, probably because such robots are still uncommon ....
J.-A. Meyer. Evolutionary approaches to neural control in mobile robots. In Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, San Diego, 1998.
Evolution of a Robust Obstacle-Avoidance Behavior in.. - Kodjabachian, Corne.. (1998) Self-citation (Meyer) (Correct)
....in these experiments is described in the text. Future research will target at furthering the incremental evolutionary process and evolving more intricate behaviors. Key words: Evolutionary robotics; Obstacle avoidance; Incremental evolution; Khepera 1 Introduction According to a recent review [26] of evolutionary approaches to neural control in mobile robots, it appears that the corresponding research efforts usually call upon a direct encoding scheme, where the phenotype of a given robot i.e. its neural controller and, occasionally, its body plan is directly encoded into its ....
J.-A. Meyer, Evolutionary approaches to neural control in mobile robots, in Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, San Diego, (October 1998) 15
Incremental Evolution of Neural Controllers for.. - Filliat.. (1999) (6 citations) Self-citation (Meyer) (Correct)
....for locomotion and obstacleavoidance in a real 6 legged SECT robot manufactured by Applied AI Systems (figure 1) Results obtained on gradient following will be published elsewhere. A review of similar approaches involving a variety of neural controllers and robots is available in Meyer [8]. 2 The SGOCE evolutionary paradigm The SGOCE evolutionary paradigm is characterized by an encoding scheme, by an evolutionary algorithm, by an incremental strategy, and by a fitness evaluation procedure that will be sketched in turn. More detailed descriptions can be found in Chavas et al. 1] ....
Meyer, J.A. "Evolutionary approaches to neural control in mobile robots." In Proceedings of the IEEE International Conference on Systems, and Cybernetics, San Diego, 1998.
Evolution of Neural Controllers for Locomotion and.. - Filliat.. (1999) (1 citation) Self-citation (Meyer) (Correct)
....that bypass human intervention insofar as possible and that more or less automatically adapt a robot s controller and morphology to the speci c problems it has to solve. The basic idea underlying such approaches to evolutionary robotics (Gomi, 1997, 1998; Higuchi et al. 1997; Husbands and Meyer, 1998), is to draw inspiration from biology and to implement a process of arti cial selection that exploits the coding of a robot s phenotype into its genotype. In three previous articles (Kodjabachian and Meyer, 1995, 1998a, 1998b) the advantages of inserting a developmental process between the ....
....to evolutionary robotics (Gomi, 1997, 1998; Higuchi et al. 1997; Husbands and Meyer, 1998) is to draw inspiration from biology and to implement a process of arti cial selection that exploits the coding of a robot s phenotype into its genotype. In three previous articles (Kodjabachian and Meyer, 1995, 1998a, 1998b) the advantages of inserting a developmental process between the genotype and the phenotype have been emphasized and a methodology implementing such a process has been developed. In particular, it has been shown how the so called SGOCE evolutionary paradigm could be used to generate ....
[Article contains additional citation context not shown here]
Meyer, J.A. (1998) Evolutionary approaches to neural control in mobile robots. In Proceedings of the IEEE International Conference on Systems and Cybernetics. San Diego.
Incremental Evolution of Neural Controllers for.. - Chavas, Corne.. (1999) (2 citations) Self-citation (Meyer) (Correct)
....are successfully downloaded on a Khepera robot. The SGOCE paradigm that is used in these experiments is described in the text. Future research will target at furthering the incremental evolutionary process and evolving more intricate behaviors. 1 Introduction According to a recent review [26] of evolutionary approaches to neural control in mobile robots, it appears that the corresponding research e orts usually call upon a direct encoding scheme, where the phenotype of a given robot i.e. its neural controller and, occasionally, its body plan is directly encoded into its genotype. ....
J.-A. Meyer, Evolutionary approaches to neural control in mobile robots, in Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, San Diego, (October 1998)
An Overview on Soft Computing in Behavior Based Robotics - Hoffmann (2003) (Correct)
No context found.
J.A. Meyer. Evolutionary approaches to neural control in mobile robots. In IEEE Int. Conference on Systems, Man and Cybernetics, 1998.
Algorithmes Volutionnistes: De L'optimisation De - Paramtres La Conception (2002) (Correct)
No context found.
Jean-Arcady Meyer. Evolutionary approaches to neural control in mobile robots. In Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, San Diego, 1998.
Evolving Neural Network Architecture and Weights - Using An Evolutionary (Correct)
No context found.
Jean-Arcady Meyer. Evolutionary approaches to neural control in mobile robots. Proc. of the IEEE Int. Conf. on Systems, Man and Cybernetics, 1998.
Continual Learning for Mobile Robots - Großmann (2001) (Correct)
No context found.
J.-A. Meyer. Evolutionary approaches to neural control in mobile robots. In Proceedings of the 1998.
Online articles have much greater impact More about CiteSeer.IST Add search form to your site Submit documents Feedback
CiteSeer.IST - Copyright Penn State and NEC