Insects, such as desert ants, employ visual homing strategies for returning to important places in their environment. A model that reproduces aspects of the insects’ navigation behavior is the “snapshot model”. It is based on the assumption that insects store a visual snapshot of the surroundings at the target location, and derive a home direction from a comparison of the current image with thi...

Autonomous mobile robots need very reliable navigation capabilities in order to operate unattended for long periods of time. We present a technique for achieving this goal that uses partially observable Markov decision process models (POMDPs) to explicitly model navigation uncertainty, including actuator and sensor uncertainty and approximate knowledge of the environment. This allows the robot ...

In the field of electronic engineering the work of automation is growing at speed of light. The fundamental concept of autonomous operation depends on technique and logic that we are using. The simple fundamental concept of operating autonomous robot or simply we can say that a mobile robot is a navigation of that robot. The navigation consists of providing the specific path to follow optimal d...

The control and coordination of multiple mobile robots is a challenging task; particularly in environments with multiple, rapidly moving obstacles and agents. This paper describes a robust approach to multi-robot control, where robustness is gained from competency at every layer of robot control. The layers are: (i) a central coordination system (MAPS), (ii) an action system (AES), (iii) a navi...

This paper describes a neural network model for the reactive behavioral navigation of a mobile robot. From the information received through the sensors the robot can elicit one of several behaviors (e.g. stop, avoid, stroll, wall following), through a competitive neural network. The robot is able to develop a control strategy depending on sensor information and learning operation. Reinforcement...

This work presents a combination of a teach-and-replay visual navigation and Monte Carlo localization methods. It improves a reliable teach-and-replay navigation method by replacing its dependency on precise dead-reckoning by introducing Monte Carlo localization to determine robot position along the learned path. In consequence, the navigation method becomes robust to dead-reckoning errors, can...

The navigation efficiency of wheeled robots needs to be further improved. Although related research has proposed various approaches, most of them describe the relationship between the robot and the obstacle roughly. Viability theory concerns the dynamic adaptation of evolutionary systems to the environment. Based on viability, we explore a method that involves robot dynamic model, environmental...