In the Robot Vision Laboratory of Purdue University , we have developed two robust architectures for vision-guided mobile robot navigation in indoor environments. The rst approach, FINALE, enables the robot to autonomously navigate in hallways at speeds around 8m=min through vision-based position-updating, utilizing a geometrical map, model-based reasoning and Kalman ltering. The performance of...

Potential function approaches to robot navigation pro vide an elegant paradigm for expressing multiple con straints and goals in mobile robot navigation problems As an example a simple reactive navigation strat egy can be generated by combining repulsion from ob stacles with attraction to a goal Advantages of this approach can also be extended to multi robot teams In this paper we present a new...

In a recent paper we have presented a method for image-based navigation by which a robot can navigate to desired positions and orientations in 3-0 space specified b y single images taken from these positions. In this paper we further investigate the method and develop robust algorithms for navigation assuming the perspective projection model. In particular, we develop a tracking algorithm that ...

The behavioral approach to robot navigation, characterized by a representation of the environment that is topological and robot-environmental interactions that are reactive, is preferable to the pure geometrical navigation because it is far more robust to unpredictable changes of the environment. Nevertheless, there is still a need to obtain geometrical maps. This paper considers a geometrical ...

The Kalman filters have been widely used for mobile robot navigation and system integration. So that it may operate autonomously, a mobile robot must know where it is. Accurate localization is a key prerequisite for successful navigation in large-scale environments, particularly when global models are used, such as maps, drawings, topological descriptions, and CAD models. This paper presents th...

This paper proposes a new fuzzy logic-based navigation method for a mobile robot moving in an unknown environment. This method allows the robot obstacles avoidance and goal seeking without being stuck in local minima. A simple Fuzzy controller is constructed based on the human sense and a fuzzy reinforcement learning algorithm is used to fine tune the fuzzy rule base parameters. The advantages ...

The purpose of this study is to present a model based on similarities in human navigation and robot navigation. It uses a hierarchical structure in three levels of landmarks, route, and survey knowledge. Recent cognitive models suggest that people use these types of spatial knowledge to perform many daily tasks. A similar approach was used for the robot navigation. The robot was able to finish ...

Mobile robot navigation in total or partially unknown environments is still an open problem. The path planning algorithms lack completeness and/or performance. Thus, there is the need for complete (i.e., the algorithm determines in finite time either a solution or correctly reports that there is none) and performance (i.e., with low computational complexity) oriented algorithms which need to pe...

This paper applies our developed novice users oriented force feedback steering wheel interface and mouse interface to navigating a tank type rescue robot. By analyzing merits and limitation of operating each interface, we propose a combined navigation strategy by the two interfaces. The steering wheel interface consists of a force feedback steering control and a six monitors’ wall. Through this...

| This paper addresses the problem of mobile robot self-localization given a polygonal map and a set of observed edge segments. The standard approach uses interpretation tree search with pruning heuristics to match observed edges to map edges. Our approach introduces a preprocessing step in which the map is decomposed into view-invariant regions (VIRs). The VIR decomposition captures informatio...