Evolving Fuzzy Uncalibrated Visual Servoing for Mobile Robots
In this paper, fuzzy models obtained on-line and off-line for uncalibrated visual servoing, are proposed and validated for an unicycle mobile robot. This approach will recursively update the inverse fuzzy model based only on measurements, at a given time
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Evolving Fuzzy Uncalibrated Visual Servoing for Mobile Robots P.J.S. Gonc¸alves, P.J.F. Lopes, P.M.B. Torres, and J.M.R. Sequeira
Abstract In this paper, fuzzy models obtained on-line and off-line for uncalibrated visual servoing, are proposed and validated for an unicycle mobile robot. This approach will recursively update the inverse fuzzy model based only on measurements, at a given time instant. The uncalibrated approach does not require calibrated kinematic and camera models, as needed in classical visual servoing to obtain the Jacobian. Experimental results obtained in an unicycle mobile robot performing eye-in-hand visual servoing are used to demonstrate the validity of the proposed approach, when compared to the previous developed off-line learning.
6.1
Introduction
Robots use sensor-based control to perform tasks, either in structured or unstructured environments. Vision sensors provide a vast amount of information on the environment in which robots move. Thus, vision is essential for robots working in unstructured environments. These types of sensor definitely enlarge the potential applications of the actual robots, mobile or manipulators, and are massively used. Visual servoing can be defined as a method to control dynamic systems using the information provided by visual sensors. In this paper, the control of a unicycle [1] mobile robot using a single camera attached to the robot (eye-in-hand) is addre-ssed [2]. P.J.S. Gonc¸alves (*) School of Technology, Polytechnic Institute of Castelo Branco, Av. Empresa´rio, 6000-767 Castelo Branco, Portugal IDMEC/LAETA, Technical University of Lisbon (TU Lisbon), Av. Rovisco Pais, 1049-001 Lisbon, Portugal e-mail: [email protected] P.J.F. Lopes • P.M.B. Torres • J.M.R. Sequeira School of Technology, Polytechnic Institute of Castelo Branco, Av. Empresa´rio, 6000-767 Castelo Branco, Portugal e-mail: [email protected]; [email protected] A. Madureira et al. (eds.), Computational Intelligence and Decision Making: Trends and Applications, Intelligent Systems, Control and Automation: Science and Engineering 61, DOI 10.1007/978-94-007-4722-7_6, # Springer Science+Business Media Dordrecht 2013
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Early approaches for visual servoing are based on a model already known, i.e. the robot-camera model, from which the relation between the image features and the robot kinematics is analytically obtained [2]. Apart from the stated approaches where the robot-camera model is already known, it can also be estimated [3]. This type of systems, Uncalibrated Visual Servoing, can deal with unknown robot kinematics and/or unknown camera parameters. By using this type of robot-camera models, the system becomes independent of robot type, camera type or even camera location. Several approaches claim to use uncalibrated visual control on a mobile robot, but the only uncalibrated part are the cameras as for example in [4]. In this paper, the robot-camera model estimation by learning is addressed both on-line and off-line, using fuzzy techniques to obtain
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