| This paper presents an adaptive method that allows mobile robots to learn cognitive maps of indoor environments incrementally and on-line. Our approach models the environment by means of a variable-resolution partitioning that discretizes the world in perceptually homogeneous regions. The resulting model incorporates both a compact geometrical representation of the environment and a topo-logi...

In this paper we show how non–linear attractor dynamics can be used as a framework to control teams of autonomous mobile robots that should navigate according to a predefined geometric formation. The environment does not need to be known a priori and may change over time. Implicit to the control architecture are some important features such as establishing and moving the formation, split and jo...

Conventional fuzzy logic controller is applicable when there are only two fuzzy inputs with usually one output. Complexity increases when there are more than one inputs and outputs making the system unrealizable. The ordinal structure model of fuzzy reasoning has an advantage of managing high-dimensional problem with multiple input and output variables ensuring the interpretability of the rule ...

This paper proposes a new approach for calibration of dead reckoning process. Using the well-known UMBmark (University of Michigan Benchmark) is not sufficient for a desirable calibration of dead reckoning. Besides, existing calibration methods, usually require explicit measurement of actual motion of the robot. Some recent methods, use the smart encoder trailer or long range finder sensors suc...

This paper proposes a new approach for calibration of dead reckoning process. Using the well-known UMBmark (University of Michigan Benchmark) is not sufficient for a desirable calibration of dead reckoning. Besides, existing calibration methods usually require explicit measurement of actual motion of the robot. Some recent methods use the smart encoder trailer or long range finder sensors such ...

The paper deals with the wireless sensor-based remote control of mobile robots motion in an unknown environment with obstacles using the Sun SPOT technology and gives the fuzzy velocity control of a mobile robot motion in an unknown environment with slopes and obstacles. The model of the vehicle has two driving wheels and the angular velocities of the two wheels are independently controlled. Wh...

We study reinforcement learning for cognitive navigation. The state space representation is constructed by unsupervised learning during exploration. As a result of learning, a stable representation of the continuous two-dimensional manifold in the high-dimensional input space is found. The representation consists of a population of localized overlapping place fields. This statespace coding is a...

The expansion of robotic systems’ performance, as well as the need for such machines to work in complex environments (hazardous, small, distant, etc.), involves the need for user interfaces which permit efficient teleoperation. Virtual Reality based interfaces provide the user with a new method for robot task planning and control: he or she can define tasks in a very intuitive way by interactin...

mobile robot navigation is one of the basic problems in robotics. in this paper, a new approachis proposed for autonomous mobile robot navigation in an unknown environment. the proposedapproach is based on learning virtual parallel paths that propel the mobile robot toward the trackusing a multi-layer, feed-forward neural network. for training, a human operator navigates themobile robot in some...