The current research sought to construct a computational model of human navigation for virtual three dimensional environments. The model was implemented within the ACT-R cognitive architecture [1]. The navigation model incorporates visual search, encoding object features and spatial relationships, motion, obstacle avoidance, and incidental visual memory.

In an application where autonomous robots can amalgamate spontaneously into arbitrary organisms, the individual robots cannot know a priori at which location in an organism they will end up. If the organism is to be controlled autonomously by the constituent robots, an evolutionary algorithm that evolves the controllers can only develop a single genome that will have to suffice for every indivi...

A critical challenge in the creation of autonomous mobile robots is the reliable detection of moving and static obstacles. In this paper, we present a passive vision system that recovers coarse depth information reliably and efficiently. This system is based on the concept of depth from focus, and robustly locates static and moving obstacles as well as stairs and dropoffs with adequate accuracy...

Most computer and robot vision algorithms, be it for object detection, recognition, or reconstruction, are designed for opaque objects. Non-opaque objects have received less attention, although various special cases have been the subject of research efforts, especially the case of specular objects. The main objective of this paper is to provide a research work in the case of semitransparent obj...

A planning methodology for nonholonomic mobile manipulators in the presence of obstacles is developed. The method employs smooth and continuous functions, such as polynomials, and it is very fast, easy to use and computationally inexpensive. The core of the method is based on mapping the nonholonomic constraint to a space where it can be satisfied trivially. In this paper, the method is first e...

This paper presents a novel method of combining topological and feature-based mapping strategies to create a hierarchical approach to simultaneous localization and mapping (SLAM). More than simply running both processes in parallel, we use the topological mapping procedure to organize local feature-based methods. The result is an autonomous exploration and mapping strategy that scales well to l...

Srinivasan and Zhang (1993) describe behavioral evidence for two distinct movement detecting systems in bee: (1) A direction selective pathway with low frequency response characteristics serving the optomotor response and (2) A non-direction selective movement system with higher frequency response serving functions of obstacle avoidance and the ‘tunnel centering’ response where the animal seeks...

We contribute a fast system for avoiding unknown obstacles on a mobile robot using a simple camera as the only sensor. The vision module detects objects, both known and unknown, around the robot. Unknown objects are detected by paying attention to occlusions of a floor of known colors. Range and angle to the objects is calculated and used to create a radial model of the robot’s vicinity. This m...

This paper presents a passivity-based controller design capable of achieving autonomous obstacle avoidance for robot manipulators subject to joint position and joint rate constraints. The control objectives are achieved by exploiting the passivity properties of the system and utilizing barrier function ideas to reshape the control Lyapunov function. The final control Lyapunov function is remini...

Autonomous ground vehicle navigation requires the integration of many technologies such as path planning, position and orientation sensing, vehicle control, and obstacle avoidance. The work presented here focuses on the control of a non-holonomic ground vehicle as it tracks a given path. A new path tracking technique called ‘vector pursuit’ is presented. This new technique is based on the theor...