Improved data association and occlusion handling for vision-based people tracking by mobile robots

This paper presents an approach for tracking multiple persons using a combination of colour and thermal vision sensors on a mobile robot. First, an adaptive colour model is incorporated into the measurement model of the tracker. Second, a new approach for detecting occlusions is introduced, using a machine learning classifier for pairwise comparison of persons (classifying which one is in front of the other). Third, explicit occlusion handling is then incorporated into the tracker

Experimental analysis of gas-sensitive Braitenberg vehicles

This article addresses the problem of localizing a static gas source in an indoor environment by a mobile robot. In contrast to previous works, the environment is not artificially ventilated to produce a strong unidirectional airflow. Here, the dominant transport mechanisms of gas molecules are turbulence and convection flow rather than diffusion, which results in a patchy, chaotically fluctuating gas distribution. Two Braitenberg-type strategies (positive and negative tropotaxis) based on the instantaneously measured spatial concentration gradient were investigated. Both strategies were shown to be of potential use for gas source localization. As a possible solution to the problem of gas source declaration (the task of determining with certainty that the gas source has been found), an indirect localization strategy based on exploration and concentration peak avoidance is suggested. Here, a gas source is located by exploiting the fact that local concentration maxima occur more frequently near the gas source compared to distant regions

Distances to the high galactic latitude molecular clouds G192-67 and MBM 23-24

We report on distance determinations for two high Galactic latitude cloud complexes, G192-67 and MBM 23-24. No distance determination exists in the literature for either cloud. Thirty-four early type stars were observed towards the two clouds, more than half of which have parallaxes measured by the Hipparcos satellite. For the remaining stars we have made spectroscopic distance estimates. The data consist of high resolution echelle spectra centered on the Na I D lines, and were obtained over six nights at the Coude Feed telescope at Kitt Peak National Observatory. Interstellar absorption lines were detected towards some of the stars, enabling estimates of the distances to the clouds of 109 +/- 14 pc for G192-67, and of 139 +/- 33 pc for MBM 23-24. We discuss the relationship of these clouds to other ISM features such as the Local Hot Bubble and the local cavity in neutral hydrogen.Comment: 15 pages, 6 embedded figures, to be published in the ApJ Vol. 516, No.

Fusion of aerial images and sensor data from a ground vehicle for improved semantic mapping

This work investigates the use of semantic information to link ground level occupancy maps and aerial images. A ground level semantic map, which shows open ground and indicates the probability of cells being occupied by walls of buildings, is obtained by a mobile robot equipped with an omnidirectional camera, GPS and a laser range finder. This semantic information is used for local and global segmentation of an aerial image. The result is a map where the semantic information has been extended beyond the range of the robot sensors and predicts where the mobile robot can find buildings and potentially driveable ground

Data association and occlusion handling for vision-based people tracking by mobile robots

This paper presents an approach for tracking multiple persons on a mobile robot with a combination of colour and thermal vision sensors, using several new techniques. First, an adaptive colour model is incorporated into the measurement model of the tracker. Second, a new approach for detecting occlusions is introduced, using a machine learning classifier for pairwise comparison of persons (classifying which one is in front of the other). Third, explicit occlusion handling is incorporated into the tracker. The paper presents a comprehensive, quantitative evaluation of the whole system and its different components using several real world data sets

Small-Scale Interstellar Na I Structure Toward M92

We have used integral field echelle spectroscopy with the DensePak fiber-optic array on the KPNO WIYN telescope to observe the central 27" x 43" of the globular cluster M92 in the Na I D wavelength region at a spatial resolution of 4". Two interstellar Na I absorption components are evident in the spectra at LSR velocities of 0 km/s (Cloud 1) and -19 km/s (Cloud 2). Substantial strength variations in both components are apparent down to scales limited by the fiber-to-fiber separations. The derived Na I column densities differ by a factor of 4 across the Cloud 1 absorption map and by a factor of 7 across the Cloud 2 map. Using distance upper limits of 400 and 800 pc for Cloud 1 and Cloud 2, respectively, the absorption maps indicate structure in the ISM down to scales of 1600 and 3200 AU. The fiber-to-fiber Na I column density differences toward M92 are comparable to those found in a similar study of the ISM toward the globular cluster M15. Overall, the structures in the interstellar components toward M92 have significantly lower column densities than those toward M15. We interpret these low column density structures as small-scale turbulent variations in the gas and compare them to the larger-scale, higher column density variations toward M15, which may be the hallmarks of actual H I structures.Comment: 9 pages, 2 figures, accepted for publication in ApJ Letter

Smelling Nano Aerial Vehicle for Gas Source Localization and Mapping

This paper describes the development and validation of the currently smallest aerial platform with olfaction capabilities. The developed Smelling Nano Aerial Vehicle (SNAV) is based on a lightweight commercial nano-quadcopter (27 g) equipped with a custom gas sensing board that can host up to two in situ metal oxide semiconductor (MOX) gas sensors. Due to its small form-factor, the SNAV is not a hazard for humans, enabling its use in public areas or inside buildings. It can autonomously carry out gas sensing missions of hazardous environments inaccessible to terrestrial robots and bigger drones, for example searching for victims and hazardous gas leaks inside pockets that form within the wreckage of collapsed buildings in the aftermath of an earthquake or explosion. The first contribution of this work is assessing the impact of the nano-propellers on the MOX sensor signals at different distances to a gas source. A second contribution is adapting the 'bout' detection algorithm, proposed by Schmuker et al. (2016) to extract specific features from the derivative of the MOX sensor response, for real-time operation. The third and main contribution is the experimental validation of the SNAV for gas source localization (GSL) and mapping in a large indoor environment (160 m²) with a gas source placed in challenging positions for the drone, for example hidden in the ceiling of the room or inside a power outlet box. Two GSL strategies are compared, one based on the instantaneous gas sensor response and the other one based on the bout frequency. From the measurements collected (in motion) along a predefined sweeping path we built (in less than 3 min) a 3D map of the gas distribution and identified the most likely source location. Using the bout frequency yielded on average a higher localization accuracy than using the instantaneous gas sensor response (1.38 m versus 2.05 m error), however accurate tuning of an additional parameter (the noise threshold) is required in the former case. The main conclusion of this paper is that a nano-drone has the potential to perform gas sensing tasks in complex environments