Real-Time Neural Control of Mobile Robots

This chapter presents two application in real-time using neural controls for mobile robots. First, a decentralized inverse optimal neural control is developed for a Shrimp robot, which is a kind of mobile robot with has terrain adaptability. Additionally, a neural control is designed for driving a nonholonomic mobile robot integrating stereo vision feedback. The desired trajectory of the robot is computed during the navigation process using the stereo camera sensor. The proposed neural control approaches are based on discrete-time High Order Neural Networks (RHONN’s) trained with an extended Kalman filter (EKF).

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