Mobile Robot Range Sensing through Visual Looming

This article describes and evaluates visual looming as a monocular range sensing method for mobile robots. The looming algorithm is based on the relationship between the displacement of a camera relative to an object, and the resulting change in the size of the object's image on the focal plane of the camera. We have carried out systematic experiments to evaluate the ranging accuracy of the looming algorithm using a Pioneer I mobile robot equipped with a color camera. We have also performed noise sensitivity for the looming algorithm, obtaining theoretical error bounds on the range estimates for given levels of odometric and visual noise, which were verified through experimental data. Our results suggest that looming can be used as a robust, inexpensive range sensor as a complement to sonar.Defense Advanced Research Projects Agency; Office of Naval Research; Navy Research Laboratory (00014-96-1-0772, 00014-95-1-0409

Mobile Robot Range Sensing through Visual Looming

This article describes and evaluates visual looming as a monocular range sensing method for mobile robots. The looming algorithm is based on the relationship between the displacement of a camera relative to an object, and the resulting change in the size of the object's image on the focal plane of the camera. We have carried out systematic experiments to evaluate the ranging accuracy of the looming algorithm using a Pioneer I mobile robot equipped with a color camera. We have also performed noise sensitivity for the looming algorithm, obtaining theoretical error bounds on the range estimates for given levels of odometric and visual noise, which were verified through experimental data. Our results suggest that looming can be used as a robust, inexpensive range sensor as a complement to sonar.Defense Advanced Research Projects Agency; Office of Naval Research; Navy Research Laboratory (00014-96-1-0772, 00014-95-1-0409

Lanthanide grafted phenanthroline-polymer for physiological temperature range sensing

Accurate measurement of the temperature is crucial as it determines the dynamics of almost any system. Conventional contact thermometers are not well suited for small scale measurements. Temperature dependent luminescent materials, i.e. materials that emit light of different color at different temperature, are therefore of particular interest in the development of noncontact thermometers. Luminescent materials consisting of lanthanide ions feature high thermal sensitivity, high photostability and high quantum yields. These ions possess very interesting light emitting properties. By anchoring them onto different backbone materials, their light absorption is increased. The search for a backbone that allows the sensor to be active in a defined temperature range, with a high detection sensitivity is ongoing. This work reports the first insoluble phenanthroline-polymer (phen-polymer) backbone on which europium (Eu3+) and terbium (Tb3+) trifluoroacetylacetone (tfac) complexes are easily grafted in a 1 : 1 metal ratio in order to create a noncontact temperature sensor. Two clear, discriminable emission peaks were observed during the photoluminescence study at room temperature, demonstrating that this material can be used as a ratiometric thermometer. The characteristic emission peak correlated to Eu3+ transition is slightly stronger than the emission peak of Tb3+ transition, resulting in a yellow emission color. The maximum value of the relative temperature sensitivity was calculated to be 2.3404% K-1 (340 K), which indicated good thermometric behavior. The emission color of the designed phen-polymer@Eu,Tb_tfac changed from light green (260 K) to orange-red (460 K). The thermometer can therefore be used as a ratiometric noncontact temperature sensor in the broad physiological temperature range

Kinect Range Sensing: Structured-Light versus Time-of-Flight Kinect

Recently, the new Kinect One has been issued by Microsoft, providing the next generation of real-time range sensing devices based on the Time-of-Flight (ToF) principle. As the first Kinect version was using a structured light approach, one would expect various differences in the characteristics of the range data delivered by both devices. This paper presents a detailed and in-depth comparison between both devices. In order to conduct the comparison, we propose a framework of seven different experimental setups, which is a generic basis for evaluating range cameras such as Kinect. The experiments have been designed with the goal to capture individual effects of the Kinect devices as isolatedly as possible and in a way, that they can also be adopted, in order to apply them to any other range sensing device. The overall goal of this paper is to provide a solid insight into the pros and cons of either device. Thus, scientists that are interested in using Kinect range sensing cameras in their specific application scenario can directly assess the expected, specific benefits and potential problem of either device.Comment: 58 pages, 23 figures. Accepted for publication in Computer Vision and Image Understanding (CVIU

Mobile robot range sensing through visual looming

This article describes and evaluates visual looming as a monocular range sensing method for mobile robots. The looming algorithm is based on the relationship between the displacement of a camera relative to an object, and the resulting change in the size of the object's image on the focal plane of the camera. We have carried out systematic experiments to evaluate the ranging accuracy of the looming algorithm using a Pioneer 1 mobile robot equipped with a color camera. We have also performed noise sensitivity for the looming algorithm, obtaining theoretical error bounds on the range estimates for given levels of odometric and visual noise, which were verified through experimental data. Our results suggest that looming can be used as a robust, inexpensive range sensor as a complement to sonar

Sensing Capacity for Markov Random Fields

This paper computes the sensing capacity of a sensor network, with sensors of limited range, sensing a two-dimensional Markov random field, by modeling the sensing operation as an encoder. Sensor observations are dependent across sensors, and the sensor network output across different states of the environment is neither identically nor independently distributed. Using a random coding argument, based on the theory of types, we prove a lower bound on the sensing capacity of the network, which characterizes the ability of the sensor network to distinguish among environments with Markov structure, to within a desired accuracy.Comment: To appear in the proceedings of the 2005 IEEE International Symposium on Information Theory, Adelaide, Australia, September 4-9, 200