30 credits – On-board Lidar based Object Detection for Autonomous Heavy Duty Vehicles

30 credits – On-board Lidar based Object Detection for Autonomous Heavy Duty Vehicles

Scania genomgår nu en transformation från att vara en leverantör av lastbilar, bussar och motorer till en leverantör av kompletta och hållbara transportlösningar.

Background
Scania is one of the worlds leading manufacturers of trucks and buses for heavy transport, as well as industrial and marine engines. Over a million Scania vehicles are in active use, in over 100 countries. Scania's mission is to shape the transport solutions of the future by introducing better transport solutions targeting autonomy, efficiency and sustainability. Among these solutions, Scanias future autonomous vehicles, with Scanias robotic platform as backbone, will be able to understand their surrounding environment and take smart manoeuvring decisions accordingly. At Scanias Autonomous Transport Solutions Pre-Development & Research department, the Sensors & Machine Learning group focuses on the development of the sensing platform and intelligent sensor data processing for our autonomous vehicles.

Description
Accurate and robust perception of driving environments is a prerequisite for autonomous driving and is dependent upon intelligent processing of vehicle sensor data. Monocular cameras and LIDARs are two types of such vehicle sensors where 3D point cloud from LIDARs provide accurate depth measurements and reflection intensity of the environment. A lot of lidar data is acquired from different lidar models (both sparse and dense) mounted at different mounting positions on our test vehicles. In this proposed project the student will be responsible for analysing and detecting objects of interest in LIDAR point clouds obtained from our very own test vehicles. The challenge for the student will be to propose a general solution for object detection which can cope with different varieties of lidar data and mounting positions.

The successful applicant will have the opportunity to gain hands-on experience of working on the latest sensors, computing platform and Scanias concept autonomous vehicles. The applicant will also have access to the knowledgeable researchers and developers working at Scanias Autonomous Transport Solutions Pre-Development & Research department.

Goals
To establish a pipeline on Scanias computational platform for the detection of challenging driving environment objects by processing of LIDAR data.
  • Calibration (if not available) of sensors on autonomous vehicles and controlled data gathering
  • To familiarize oneself with algorithm development on Scanias computational platform
  • To survey the latest algorithms for lidar based object detection
  • Implementation of a suitable algorithm and experimental validation for object detection
We are open to the exploration of innovative ideas and if feasible the applicant might also get a chance to submit her/his results to a reputable research conference.

Applicants
One thesis worker studying a Masters program in Computer Science, Electrical Engineering or similar. Applicants are expected to have a good understanding of signal processing, computer vision and practice thereof. The applicant should have sufficient software development knowledge to be able to implement proposed mathematical concepts. Prior experience with 3D point cloud handling is a plus. The applicant should be able to work in a diverse environment and communicate effectively in English. The personal traits of being agile, giving/receiving constructive feedback and taking initiatives will come handy.

Time plan
The project is planned for 20 weeks and can be started any time in early Spring 2018.
Applicants will be assessed on continuous basis until the position is filled.

Communication of the results
The results will be described in a report, published on Scanias internal web and by the applicants university, and be shown in presentations at Scania. The prototype tool will be made available to Scania.

Organisation
The project will be performed within Scanias Autonomous Transport Solutions Pre-Development & Research department.

Contacts
Nazre Batool, Development Engineer, Sensors and Machine Learning Team, Autonomous Transport Solutions, nazre.batool@scania.com
Per Sahlholm, Head of Sensors and Machine Learning Team, Autonomous Transport Solutions, per.sahlholm@scania.com
Mer info
Område Södertälje
Yrkesroll Teknik & Ingenjör
Typ av anställning Heltid
Hemsida http://www.scania.com
Sista ansökningsdag 30 nov (12 dagar kvar)

Om arbetsgivaren

Scania är en världsledande leverantör av transportlösningar. Tillsammans med våra partners och kunder leder vi övergången till ett hållbart transportsystem. Under 2017 levererade vi 82 500 lastbilar, 8 300 bussar samt 8 500 industri- och marinmotorer till våra kunder. Vi omsatte närmare 120 miljarder kronor, varav 20 procent utgjordes av servicerelaterade tjänster. Scania grundades 1891 och finns idag representerat i mer än 100 länder, och har drygt 49 000 medarbetare. Forskning och utveckling är koncentrerad till Sverige, med filialer i Brasilien och Indien. Produktion sker i Europa, Latinamerika och Asien, med regionala produktcentra i Afrika, Asien och Eurasien. Scania ingår i Traton Group. För ytterligare information, besök www.scania.com.