LiDAR and Camera Detection Fusion in a Real Time Industrial Multi-Sensor Collision Avoidance System

Collision avoidance is a critical task in many applications, such as ADAS (advanced driver-assistance systems), industrial automation and robotics. In an industrial automation setting, certain areas should be off limits to an automated vehicle for protection of people and high-valued assets. These areas can be quarantined by mapping (e.g., GPS) or via beacons that delineate a no-entry area. We propose a delineation method where the industrial vehicle utilizes a LiDAR {(Light Detection and Ranging)} and a single color camera to detect passive beacons and model-predictive control to stop the vehicle from entering a restricted space. The beacons are standard orange traffic cones with a highly reflective vertical pole attached. The LiDAR can readily detect these beacons, but suffers from false positives due to other reflective surfaces such as worker safety vests. Herein, we put forth a method for reducing false positive detection from the LiDAR by projecting the beacons in the camera imagery via a deep learning method and validating the detection using a neural network-learned projection from the camera to the LiDAR space. Experimental data collected at Mississippi State University's Center for Advanced Vehicular Systems (CAVS) shows the effectiveness of the proposed system in keeping the true detection while mitigating false positives.Comment: 34 page

Productivity and evapotranspiration of two contrasting semiarid ecosystems following the 2011 global carbon land sink anomaly

© 2016 Elsevier B.V. Global carbon balances are increasingly affected by large fluctuations in productivity occurring throughout semiarid regions. Recent analyses found a large C uptake anomaly in 2011 in arid and semiarid regions of the southern hemisphere. Consequently, we compared C and water fluxes of two distinct woody ecosystems (a Mulga (Acacia) woodland and a Corymbia savanna) between August 2012 and August 2014 in semiarid central Australia, demonstrating that the 2011 anomaly was short-lived in both ecosystems. The Mulga woodland was approximately C neutral but with periods of significant uptake within both years. The extreme drought tolerance of Acacia is presumed to have contributed to this. By contrast, the Corymbia savanna was a very large net C source (130 and 200gCm-2yr-1 in average and below average rainfall years, respectively), which is likely to have been a consequence of the degradation of standing, senescent biomass that was a legacy of high productivity during the 2011 anomaly. The magnitude and temporal patterns in ecosystem water-use efficiencies (WUE), derived from eddy covariance data, differed across the two sites, which may reflect differences in the relative contributions of respiration to net C fluxes across the two ecosystems. In contrast, differences in leaf-scale measures of WUE, derived from 13C stable isotope analyses, were apparent at small spatial scales and may reflect the different rooting strategies of Corymbia and Acacia trees within the Corymbia savanna. Restrictions on root growth and infiltration by a siliceous hardpan located below Acacia, whether in the Mulga woodland or in small Mulga patches of the Corymbia savanna, impedes drainage of water to depth, thereby producing a reservoir for soil moisture storage under Acacia while acting as a barrier to access of groundwater by Corymbia trees in Mulga patches, but not in the open Corymbia savanna

A Design Methodology for a High Power Density, Voltage Boost, Resonant DC-DC converter

A full-bridge, parallel-loaded, resonant, zero current/zero voltage switching converter has been developed for DC-DC voltage transformation. The power supply was used to condition power sourced by a 28-V, 400-A Neihoff alternator installed in a HMMWV that delivered power to a 5-kW mobile radar. This design focuses on achieving maximum power density at reasonable efficiency (i.e. \u3e 80%) by operating at the highest resonant and switching frequencies possible. A resonant frequency of 392-kHz was achieved while providing rated power. The high resonant frequency was facilitated by the development of an extremely low inductance layout (\u3c 20 nH) capable of conducting the high resonant currents associated with this converter topology. A design methodology is presented for parallel-loaded, resonant voltage boost converters utilizing the development of a converter prototype as a basis. The experimental results are presented as validation of the methodology

LiDAR and Camera Detection Fusion in a Real-Time Industrial Multi-Sensor Collision Avoidance System

Collision avoidance is a critical task in many applications, such as ADAS (advanced driver-assistance systems), industrial automation and robotics. In an industrial automation setting, certain areas should be off limits to an automated vehicle for protection of people and high-valued assets. These areas can be quarantined by mapping (e.g., GPS) or via beacons that delineate a no-entry area. We propose a delineation method where the industrial vehicle utilizes a LiDAR (Light Detection and Ranging) and a single color camera to detect passive beacons and model-predictive control to stop the vehicle from entering a restricted space. The beacons are standard orange traffic cones with a highly reflective vertical pole attached. The LiDAR can readily detect these beacons, but suffers from false positives due to other reflective surfaces such as worker safety vests. Herein, we put forth a method for reducing false positive detection from the LiDAR by projecting the beacons in the camera imagery via a deep learning method and validating the detection using a neural network-learned projection from the camera to the LiDAR space. Experimental data collected at Mississippi State University’s Center for Advanced Vehicular Systems (CAVS) shows the effectiveness of the proposed system in keeping the true detection while mitigating false positives

Analysis and Design of an Electric Machine Employing a Special Stator With Phase Winding Modules and PMs and a Reluctance Rotor

This paper introduces a new motor design for traction applications that achieves high power density and meets the power density target of 50kW/L target set by the US Department of Energy. The proposed motor has a doubly salient structure with concentrated toroidal 3-phase windings and permanent magnets (PMs) in the stator and a reluctance rotor, improves torque capability and operating speed compared to traditional designs. A design optimization process was conducted to balance efficiency, power density, and power factor. An equivalent circuit in the DQ reference frame is introduced to enable vector control for the proposed special double salient machine. The resulting design was validated through the creation of an open frame lab prototype (OFLP) and an experimental dyno test bench was developed. The prototype was tested through open circuit tests, static torque tests, and unity power factor tests. This paper also discusses the use of synchronous reference frame theory and per-phase diagrams to calculate electric machine parameters. In addition to experimentation, 3D and 2D electromagnetic FEA simulations have been performed for unity power factor operation as a generator to numerically separate the power loss components