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Intelligent Drivable Area Detection System Using Camera and LiDAR Sensor for an Autonomous Vehicle
No full textAutonomous vehicle has many challenging tasks to perform and navigation is one among them, since various types of road scenarios in real urban environments have to be considered, particularly when only perception sensors are used, without position information. The cars available in the market have Camera and Radar sensors mounted in them using which some of ADAS features such as Lane Keep Assist (LKA), Blind spot detection, Reverse navigation, etc. are performed. These features assist the drivers for safe driving. Automobile manufacturers are trying to bring in other different sensors such as LiDAR, GPS, IMU, etc. to make autonomous car robust. We propose a sensor fusion method by utilizing LiDAR and Camera sensor together to develop a robust drivable road detection system. In this research, the edge detection and color based segmentation techniques has been used to generate the binary image of lanes from camera sensor image. Then using RANSAC algorithm, lines can be fitted on the generated binary image to find the lane marking. But there are many roads in urban area where only one side lane marking is present and sometimes no lane marking at all. In those places, the drivable road detection system would not be able to perform well and does not know its boundary for the vehicle to drive. The sensor fused method proposed utilizes the LiDAR sensor information along with camera images to know its trajectory for safe travel. The algorithm works very well in different road scenarios in an urban area where the road contains two lane marks, one side lane with other side curb and finally on both side curbs. The proposed method was tested with two different datasets. The overall results show that the proposed algorithm performs robustly well and the system was able to identify its drivable region accurately
Electrical Property of Polypropylene Films Subjected to Different Temperatures and DC Electric Fields
No full textA polypropylene (PP) film is usually used as a dielectric material in capacitors as well as cables. However, PP films may degrade because of the combined effect of temperature and electric field. In an earlier study, plain PP films and PP films loaded with nano-metric natural clay were studied under sinusoidal (AC) electric fields at power frequency and temperatures above the ambient. To better understand the electrical characteristics of PP film under various conditions, the objective of this study is to determine the time-to-breakdown of the plain PP and PP filled with 2% (wt) natural nano-clay when subjected to time-invariant (DC) electric fields at elevated temperatures. In order to achieve this objective, the effects of uniform as well as non-uniform electric fields were compared at the same temperature for the PP film. In this study, experimental results indicated that the time-to-breakdown of all PP films, plain or filled with nano-clay, decreases with the increase in electric field intensity, non-uniformity of the electric field, and temperature. It was also found that the time-to-breakdown of PP film filled with 2% (wt) natural nano-clay under DC electric field is longer and less sensitive to temperature. Furthermore, when compared with the results under the uniform electric field, PP film filled with 2% (wt) nano-metric natural clay indicates shorter time-to-failure under non-uniform DC electric fields. Finally, the morphology of the samples was observed by digital camera, optical micrography, and SEM, to better understand the mechanism of the breakdow
2/10/2021: IME-412 Applied Control Systems Design
No full textA course designed to introduce students to various computer-controlled systems used for industrial automation including data collection, analysis and reporting. Various hardware, software, sensors, and human resources required to implement effective control systems will be studied. Students will be engaged in hands-on laboratory exercises requiring them to configure and write programs and design systems to solve various assigned problems through individual and/or group efforts. Modern techniques for Industry 4.0 such as data management for predictive maintenance and artificial intelligence will also be explored
2/17/2021: Course Change Form CS 661
No full textThe change or pre-req from CS 641 Foundations in Data Science to CS 601 Programming Methods for Data Science or BS in CS or Equivalent recognizes that the real content needed for 661 is strong programming skills, rather than the knowledge in 641. The new pre-req parallels the pre-req for the coupled undergraduate version CS 461 which has CS 102 Computing and Algorithms II as its pre-req
3/10/2021: Section 6.12.3 Faculty Handbook
No full textSection Outline:
Parties Section Rationale Reorganization Procedure Affecting Faculty Tenured Faculty Rights in Reorganizatio
