In this article we present a novel, hybrid graph spatial representation for robot navigation. This representation enables our mobile robot to build a model of its surroundings which it can then use for navigation. The models or maps that use this representation are hybrid graphs, the nodes being analogical local maps of landmark locations in the robot’s environment, the arcs being the actions t...

In this paper, we propose and validate a framework for visual navigation with collision avoidance for a wheeled mobile robot. Visual navigation consists of following a path, represented as an ordered set of key images, which have been acquired by an on-board camera in a teaching phase. While following such path, the robot is able to avoid obstacles which were not present during teaching, and wh...

This paper presents a 3-D local map building approach for real-time obstacle avoidance using visually-recognized laser patterns. Precise estimate of the local map provides essential information for navigation and control of a mobile robot in unknown environments. Existing navigation and control approaches typically require expensive sensing devices, such as sonar or laser range finder. In this ...

This paper describes XFRMLEARN, a system that learns symbolic behavior specifications to control and improve the continuous sensor-driven navigation behavior of an autonomous mobile robot. The robot is to navigate between a set of predefined locations in an office environment and employs a navigation system consisting of a path planner and a reactive collision avoidance system. XFRMLEARN ration...

This paper describes XFRMLEARN, a system that learns symbolic behavior specifications to control and improve the continuous sensor-driven navigation behavior of an autonomous mobile robot. The robot is to navigate between a set of predefined locations in an office environment and employs a navigation system consisting of a path planner and a reactive collision avoidance system. XFRMLEARN ration...

Many environment specific methods and systems for Robot Navigation exist. However vast strides in the evolution of navigation technologies and system techniques create the need for a general unified framework that is scalable, modular and dynamic. In this paper a Unified Framework for a Robust Conflict-free Robot Navigation System that can be used for either a structured or unstructured and ind...

Developing techniques for mobile robot navigation constitutes one of the major trends in the current research on mobile robotics. This paper develops a local model network (LMN) for mobile robot navigation. The LMN represents the mobile robot by a set of locally valid submodels that are Multi-Layer Perceptrons (MLPs). Training these submodels employs Back Propagation (BP) algorithm. The paper p...

Decision-theoretic reasoning and planning algorithms are increasingly being used for mobile robot navigation, due to the signi cant uncertainty accompanying the robots' perception and action. Such algorithms require detailed probabilistic models of the environment of the robot and it is very desirable to automate the process of compiling such models by means of autonomous learning algorithms. T...

This paper proposes a new hierarchical formulation of POMDPs for autonomous robot navigation that can be solved in real-time, and is memory efficient. It will be referred to in this paper as the Robot Navigation Hierarchical POMDP (RN-HPOMDP). The RN-HPOMDP is utilized as a unified framework for autonomous robot navigation in dynamic environments. As such, it is used for localization, planning ...

An adaptive-resonance theory (ART)-based fuzzy controller is presented for the adaptive navigation of a quadruped robot in cluttered environments, by incorporating the capability of ART in stable category recognition into fuzzy-logic control for selecting the adequate rule base. The environment category and the navigation mechanism are first described for the quadruped robot. The ART-based fuzz...