This paper presents a sensor system for robot localization based on the information obtained from a single camera attached in a fixed place external to the robot. Our approach firstly obtains the 3D geometrical model of the robot based on the projection of its natural appearance in the camera while the robot performs an initialization trajectory. This paper proposes a structure-from-motion solution that uses the odometry sensors inside the robot as a metric reference. Secondly, an online localization method based on a sequential Bayesian inference is proposed, which uses the geometrical model of the robot as a link between image measurements and pose estimation. The online approach is resistant to hard occlusions and the experimental setup proposed in this paper shows its effectiveness in real situations. The proposed approach has many applications in both the industrial and service robot fields.
This paper describes the theoretical and practical foundations for remote control of a mobile robot for nonlinear trajectory tracking using an external localisation sensor. It constitutes a classical networked control system, whereby event-based techniques for both control and state estimation contribute to efficient use of communications and reduce sensor activity. Measurement requests are dictated by an event-based state estimator by setting an upper bound to the estimation error covariance matrix. The rest of the time, state prediction is carried out with the Unscented transformation. This prediction method makes it possible to select the appropriate instants at which to perform actuations on the robot so that guidance performance does not degrade below a certain threshold. Ultimately, we obtained a combined event-based control and estimation solution that drastically reduces communication accesses. The magnitude of this reduction is set according to the tracking error margin of a P3-DX robot following a nonlinear trajectory, remotely controlled with a mini PC and whose pose is detected by a camera sensor.
This paper presents a reflector recognition and localization technique in three-dimensional (3-D) environments, using only times-of-flight (TOFs) data obtained from ultrasonic transducers. The recognition and localization technique is based on the principal component analysis applied to the TOF vectors originating from a sensor that contains two emitting transducers and several receivers. The two emitters simultaneously transmit two coded pulses that are detected later on and discriminated by the receivers, after being reflected in the environment. The proposed technique allows for the possibility of not only recognizing the reflectors, but also estimating approximately its localization referred to the sensor. This technique has been tested with three types of reflectors in 3-D environments: planes, edges, and corners. The achieved results are very satisfactory for reflectors located in the range 50-350 cm.
Abstract. This paper describes a wheelchair for physically disabled people developed within the UMIDAM I Project. A dependent-user recognition voice system and ultrasonic and infrared sensor systems has been integrated in this wheelchair. In this way we have obtained a wheelchair which can be driven with using voice commands and with the possibility of avoiding obstacles and downstairs or hole detection. The wheelchair has also been developed to allow autonomous driving (for example, following walls). The project, in which two prototypes have been produced, has been carried out totally in the Electronics Department of the University of Alcalfi (Spain). It has been financed by the ONCE 2. Electronic system configuration, a sensor system, a mechanical model, control (low level control, control by voice commands), voice recognition and autonomous control are considered. The results of the experiments carried out on the two prototypes are also given.
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