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Master Thesis: “Intelligent Dynamic Occupancy Grid

Intel


Location:
Karlsruhe, DE
Date:
09/20/2017
2017-09-202017-10-19
Job Code:
JR0033874
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Job Details

Master Thesis: “Intelligent Dynamic Occupancy Grid Careers at Intel in Karlsruhe,
   
Job ID: JR0033874
Job Category: Intern/Student
Primary Location: Karlsruhe, DE
Other Locations:
Job Type: Intern

Master Thesis: “Intelligent Dynamic Occupancy Grid

Job Description
One important component of Automated Driving is environmental perception. AD cars will have several sensors including laser scanner, radar and ultrasonic sensors and mono cameras. In the perception part the information from all these sensors have to be fused together to obtain a model of the environment. In the past object detection and tracking was mostly solved by object 'Bounding box' approaches. These approaches are known to be limited in multiple aspects. Therefore, additionally grid based approaches were combined to model the static environment. Recently some approaches become available that can simultaneously fuse the information from the different sensors and detect static and dynamic objects and free spaces. Deep Learning approaches are very successful and applied in lots of fields, e.g. to predict object behavior. We are providing the opportunity to work on information fusion by using a model based Dynamic Occupancy Grid and Deep Learning approaches.Below are the steps we expect the candidate will pass during the work on the topic:Literature reviewAlgorithmic development of grid based sensor fusion approachImplementationEvaluation of the algorithm on real dataPerformance analysis of the implemented algorithm Optimization


Qualifications

Completed Bachelor or equivalent degree in Information Technology or Electrical EngineeringInterest in ADBasic knowledge in image processing, CV, machine learningProgramming languages: MatlabTM, C/C++Good English skillsGerman language skills are not mandatory but advantageous

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