Position control system with fuzzy microprocessor AL220

2005

Abstract. We differentiate surfaces with different properties with simple low-cost IR emitters and detectors in a location-invariant manner. The intensity readings obtained with such sensors are highly dependent on the location and properties of the surface, which complicates the differentiation and localization process. Our approach, which models IR intensity scans parametrically, can distinguish different surfaces independent of their positions. Once the surface type is identified, its position (r,) can also be estimated. The method is verified experimentally with wood; Styrofoam packaging material; white painted matte wall; white and black cloth; and white, brown, and violet paper. A correct differentiation rate of 100% is achieved for six surfaces, and the surfaces are localized within absolute range and azimuth errors of 0.2 cm and 1.1 deg, respectively. The differentiation rate decreases to 86% for seven surfaces and to 73% for eight surfaces. The method demonstrated shows that simple IR sensors, when coupled with appropriate signal processing, can be used to recognize different types of surfaces in a location-invariant manner.

Section: Introductionmentioning

confidence: 99%

Surface differentiation by parametric modeling of infrared intensity scans

2005

“…[10][11][12][13][14][15][16] IR sensors are used in robotics and automation, process control, remote sensing, and safety and security systems. More specifically, they have been used in simple object and proximity detection, 17 counting, 18 distance and depth monitoring, 19 floor sensing, position measurement, and control, 20,21 obstacle/collision avoidance, 22,23 and map building. 24 IR sensors are used in door detection and mapping of openings in walls, 25 as well as monitoring doors/ windows of buildings and vehicles, and ''light curtains'' for protecting an area.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous extraction of geometry and surface properties of targets using simple infrared sensors

2004

Abstract. We investigate the use of low-cost infrared (IR) sensors for the simultaneous extraction of geometry and surface properties of commonly encountered features or targets in indoor environments, such as planes, corners, and edges. The intensity measurements obtained from such sensors are highly dependent on the location, geometry, and surface properties of the reflecting target in a way that cannot be represented by a simple analytical relationship, therefore complicating the localization and recognition process. We propose the use of angular intensity scans and present an algorithm to process them to determine the geometry and the surface type of the target and estimate its position. The method is verified experimentally with planes, 90-deg corners, and 90-deg edges covered with aluminum, white cloth, and Styrofoam packaging material. An average correct classification rate of 80% of both geometry and surface over all target types is achieved and targets are localized within absolute range and azimuth errors of 1.5 cm and 1.1 deg, respectively. Taken separately, the geometry and surface type of targets can be correctly classified with rates of 99 and 81%, respectively, which shows that the geometrical properties of the targets are more distinctive than their surface properties, and surface determination is the limiting factor. The method demonstrated shows that simple IR sensors, when coupled with appropriate processing, can be used to extract substantially more information than that for which such devices are commonly employed.

“…More specifically, infrared sensors have been used in simple object and proximity detection, counting, 1,2 distance and depth monitoring, 3 floor sensing, position control, 4 obstacle and collision avoidance, 5 and machine vision systems. 6 Infrared sensors are used in door detection, 7 mapping of openings in walls, 8 monitoring doors and windows of buildings and vehicles, and light curtains for protecting an area.…”

Section: Introductionmentioning

confidence: 99%

Rule-based target differentiation and position estimation based on infrared intensity measurements

2003

Abstract. This study investigates the use of low-cost infrared sensors in the differentiation and localization of target primitives commonly encountered in indoor environments, such as planes, corners, edges, and cylinders. The intensity readings from such sensors are highly dependent on target location and properties in a way that cannot be represented in a simple manner, making the differentiation and localization difficult. We propose the use of angular intensity scans from two infrared sensors and present a rule-based algorithm to process them. The method can achieve position-invariant target differentiation without relying on the absolute return signal intensities of the infrared sensors. The method is verified experimentally. Planes, 90-deg corners, 90-deg edges, and cylinders are differentiated with correct rates of 90%, 100%, 82.5%, and 92.5%, respectively. Targets are localized with average absolute range and azimuth errors of 0.55 cm and 1.03 deg. The demonstration shows that simple infrared sensors, when coupled with appropriate processing, can be used to extract a significantly greater amount of information than they are commonly employed for.