Using infrared sensors for distance measurement in mobile robots

Moving towards autonomy, unmanned vehicles rely heavily on state-of-the-art collision avoidance systems (CAS). A lot of work is being done to make the CAS as safe and reliable as possible, necessit ...

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Unmanned Aerial Vehicles (UAVs) : Collision Avoidance Systems and Approaches

Sophisticated methods for true spectral rendering have been developed in computer graphics to produce highly accurate images. In addition to traditional applications in visualizing appearance, such methods have potential applications in many areas of scientific study. In particular, we are motivated by the application of studying avian vision and appearance. An obstacle to using graphics in this application is the lack of reliable input data. We introduce an end-to-end measurement system for capturing spectral data on 3D objects. We present the modification of a recently developed hyperspectral imager to make it suitable for acquiring such data in a wide spectral range at high spectral and spatial resolution. We capture four megapixel images, with data at each pixel from the near-ultraviolet (359 nm) to near-infrared (1,003 nm) at 12 nm spectral resolution. We fully characterize the imaging system, and document its accuracy. This imager is integrated into a 3D scanning system to enable the measurement of the diffuse spectral reflectance and fluorescence of specimens. We demonstrate the use of this measurement system in the study of the interplay between the visual capabilities and appearance of birds. We show further the use of the system in gaining insight into artifacts from geology and cultural heritage.

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3D imaging spectroscopy for measuring hyperspectral patterns on solid objects

The amplitude response of infrared (IR) sensors depends on the reflectance properties of the target. Therefore, in order to use IR sensor for measuring distances accurately, prior knowledge of the surface must be known. This paper describes the Phong Illumination Model for determining the properties of a surface and subsequently calculating the distance to the surface. The angular position of the IR sensor is computed as normal to the surface for simplifying the calculation. Ultrasonic (US) sensor can provide the initial information on distance to obtain the parameters for this method. In addition, the experimental results obtained by using LabView are discussed. More care should be taken when placing the objects from the sensors during acquiring data since the small change in angle could show very different distance than the actual one. Since stereo camera vision systems do not perform well under some environmental conditions such as plain wall, glass surfaces, or poor lighting conditions, the IR and US sensors can be used additionally to improve the overall vision systems of mobile robots. Keywords—Distance Measurement, Infrared sensor, Surface properties, Ultrasonic sensor.

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Using Ultrasonic and Infrared Sensors for Distance Measurement

Autonomous vehicles (AVs) must share space with pedestrians, both in carriageway cases such as cars at pedestrian crossings and off-carriageway cases such as delivery vehicles navigating through crowds on pedestrianized high-streets. Unlike static obstacles, pedestrians are active agents with complex, interactive motions. Planning AV actions in the presence of pedestrians thus requires modelling of their probable future behavior as well as detecting and tracking them. This narrative review article is Part I of a pair, together surveying the current technology stack involved in this process, organising recent research into a hierarchical taxonomy ranging from low-level image detection to high-level psychology models, from the perspective of an AV designer. This self-contained Part I covers the lower levels of this stack, from sensing, through detection and recognition, up to tracking of pedestrians. Technologies at these levels are found to be mature and available as foundations for use in high-level systems, such as behavior modelling, prediction and interaction control.

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Pedestrian Models for Autonomous Driving Part I: Low-Level Models, From Sensing to Tracking

Sensors based on the ultrasonic, pulse-echo technique for measuring range have been the mainstay for robotic collision avoidance systems. Although these sensors have been successfully applied to both indoor and outdoor mobile robotic applications, certain disadvantages of these systems prompted our investigation of inexpensive sensors that use light to determine the range or presence of targets. A number of commercially available, light-based sensors are analyzed for application in a mobile robotic space application. The objective of the analysis is to develop a cost-effective, light-based ranging sensor for a collision avoidance system for an experimental Mars Rover. This paper presents some results from our investigation. >

Active infrared sensors for mobile robots

This paper investigates modeling indoor environments using a low-cost, compact, active-range camera, known as BIRIS, mounted onto a pan and tilt motor unit. The BIRIS sensor, developed at the National Research Council of Canada, is a rugged small camera with no moving parts. The objectives of this paper are to describe and demonstrate the viability of the use of a low-cost range sensor in the domain of indoor environment modeling; to present the results of processing three-dimensional (3-D) data to build a virtual environment for navigation and visualization; and, to analyze and outline the advantages and limitations encountered when scanning large indoor environments.

Active range sensing for indoor environment modeling

This paper investigates modeling indoor environments using a low-cost compact active range camera, known as BIRIS, mounted onto a pan and tilt motor unit. The BIRIS sensor, developed at the National Research Council of Canada, is a rugged small camera with no moving parts. The contributions of this paper are mainly in three areas: it demonstrates the viability of the use of a low-cost range sensor in the domain of indoor environment modeling; it presents the of processing 3-D data to build a virtual environment for navigation and visualization; and, it analyses and outlines the advantages and and limitations encountered when scanning large indoor environments.

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S. Elgazzar

Papers

Active infrared sensors for mobile robots

Active range sensing for indoor environment modeling

3D data acquisition for indoor environment modeling using a compact active range sensor