A flexible architecture for intelligent cruise control

Handmann, Uwe; Leefken, Iris; Tzomakas, Christos; Seelen, Werner von

doi:10.1109/itsc.1999.821193

Cited by 12 publications

(1 citation statement)

References 6 publications

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“…There have been numerous studies of object recognition in a robotic manipulation context. [3] developed an intelligent cruise control (ICC). Object recognition based on sensor data was part of their intelligent system and they made great contributions but mainly on car tracking systems, which were far from our research problems.…”

Section: Scene Analysismentioning

confidence: 99%

Genetic Tuner for Image Classification with Robotic Applications

Jafari¹,

Jarvis²

2005

Proceedings of the 1st International Workshop on Artificial Neural Networks and Intelligent Information Processing

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This paper introduces a genetic tuner implemented for optimizing the image scene analysis prior to the grasping of the objects, to realize a concrete working robot named COERSU 1. Firstly, different architectures of the adaptive neuro-fuzzy inference system, multi-layer perceptron and K-nearest neighborhood classifiers are compared to perform scene analysis and object recognition. Following on, the MLP classifier is chosen due to its accuracy and flexibility to be tuned by genetic algorithm. The real-time experiments (after tuning) show that the performance of the genetically tuned MLP classifier is improved in terms of accuracy due to this hybridization. Finally, snapshots of the experimental results from COERSU in a table-top scenario to manipulate some soft objects (e.g. fruit/egg) are provided to validate the methods.

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Section: Scene Analysismentioning

confidence: 99%