The problem of determining the pose (position and orientation) of a sensor in an unknown environment by incrementally building up a map of the environment is known as Simultaneous Localisation and Mapping (SLAM) in robotics. Currently, the focus for SLAM work has been done on sensors such as laser rangefinders and sonar with very little work on using vision as a sensor. This paper investigates ...

The two-robot entry from the University of South Florida received a Technical Innovation Award for Conceptual and Artistic Design in the Hors d’Oeurves Anyone? event of the 1999 AAAI Mobile Robot Competition. The entry was fielded by a team of seven students from the Computer Science and Engineering and Art departments. Three of the team members were undergraduates. The robots were unique in th...

Mobile robots play a prominent role in many industrial applications to simplify the job of an individual. While they are used extensively in the industry and household applications, one prevailing challenge in mobile robots navigation in presence of dense obstacles. Identifying this challenge, this paper proposes an efficient and dynamic algorithm for accurate mobile robot navigation through a ...

Topological maps represent the world as a network of nodes and arcs: the nodes are distinctive places in the environment and the arcs represent paths between places. A significant issue in building topological maps is defining distinctive places. Most previous work in topological mapping has concentrated on using sonar sensors to define distinctive places. However, sonar sensors are limited in ...

Multistatic active sonar systems are being developed for the mission of tracking enemy submarines in harsh underwater environments. This paper will focus on a revolutionary new method with which to track a target. A fuzzy logic based tracker has been developed which performs remarkably better than a Kalman filter tracker. This is accomplished through the use of additional, non-kinematic informa...

Wide-angle sonar mapping of the environ­ ment by mobile robot is nontrivial due to sev­ eral sources of uncertainty: dropouts due to "specular" reflections, obstacle location un­ certainty due to the wide beam, and distance measurement error. Earlier papers address the latter problems, but dropouts remain a problem in many environments. We present an approach that lifts the overoptimistic in­ d...

An autonomous mobile robot operating in an unknown indoor environment often needs to map the environment while localising within the map. Feature-based world models including line and point features are widely used by researchers. This paper presents a novel delayed classification algorithm to categorize these features using a recently developed high performance sonar ring within a Simultaneous...

The Subsurface Autonomous Mapping System (SAMS) is a full-ocean-depth (6000-meter) autonomous vehicle with integrated physical oceanography and bottommapping sensors. Developed for the Naval Oceanographic Office (NAVOCEANO) by the Woods Hole Oceanographic Institution Ocean Systems Laboratory, SAMS is a new NAVOCEANO capability for deep-sea oceanographic data collection. SAMS is equipped with a ...

A sensor system for an underwater vehicle is described. The vehicle is equipped with inclinometers, gyroscopes, a magnetometer, a pressure gauge, and a sonar system. The sensor models used for the inclinometers and gyroscopes are straightforward; however, the magnetometer can be corrupted by variations in the earth’s field caused by: external objects and internal magnetic fields. We show how to...

To localize an underwater object, we measure the distance to this object from several sonar sensors with known locations. The problem is that the signal sent by some of the sonars is reflected not by the desired object(s), but by some auxiliary object and thus, the values measured by these sensors are drastically different from the distance to the desired object. To solve this problem, currentl...