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In this work, we propose the integration of two of the most widely used approaches for the implementation of autonomous navigation systems: the reinforcement learning for path finding, along with SLAM (Simultaneous Localization and Mapping) type algorithms for localization and mapping of the environment. These two approaches are integrated to address the problem of how a robot should explore an unknown and dynamic environment while it collects perception features in order to locate itself and, at the same time, to obtain information clues about cost traversability of an area. So, when a robot is exploring and mapping with a SLAM algorithm it is also learning to associate perception features with costs and actions to find optimal paths from the starting point to the goal point in dynamical environments. [ABSTRACT FROM PUBLISHER]

A bilateral teleoperator is composed of a local and a remote manipulators interconnected through a communication channel. A human operator interacts with the local manipulator to remotely execute a given task via the remote manipulator and the interaction of the remote manipulator with the remote environment is reflected back to the human operator. Thus, the control objective is to establish local and remote position synchronization. This paper employs adaptive control techniques, that can achieve the desired control objective, to an experimental setup composed of two nonlinear manipulators. In these novel experimental results the local and remote manipulators are located in Guadalajara, Mexico, and in Barcelona, Spain, respectively. The manipulators are two Sensable's PHANToM Omni® devices and are interconnected through the Internet. It is shown, experimentally, that the adaptive controllers provide asymptotic stability of the local and remote position error even in the presence of variable time-delays. [ABSTRACT FROM PUBLISHER]

This paper presents a new visual servo controller based on geometric algebra (GA). The controller has an angular and translational components that are designed using rotors and translators. The controller does not require additional calculations or jacobian-like matrices. We modify the controller to regulate a mobile robot with three degrees of freedom controllable by two. The proposed controller is applied to a nonholonomic mobile robot with a camera mounted on it. The position of the robot is regulated from its current position to a desired position using current and desired images. We develop a GA-based Lyapunov function to demonstrate the stability of the controller and we present simulations validating the proposed controller. [ABSTRACT FROM PUBLISHER]

The output-feedback design problem for a bilateral teleoperator scheme is considered. The recently proposed Immersion and Invariance (I&I) observer is used to obtain an exponentially convergent estimate of the unmeasured velocities. Moreover, it is proven that when this observer is interconnected to the nonlinear teleoperator together with a Proportional plus damping (P+d) controller, the overall system is globally stable. Finally, in the case when the human operator and the environment do not exert forces on the local and remote manipulator, respectively, global asymptotic convergence to zero of the velocities and of the position tracking error is achieved. These results are obtained by introducing two important design modifications ensuring the explicit derivation of the observer dynamics and that the interconnected system inherits the same stability properties as in the full-measurement case. The theoretical results are illustrated with simulations using local and remote two degree-of-freedom nonlinear manipulators. [ABSTRACT FROM PUBLISHER]