caor@mines-paristech.fr

Sensor fusion for unsupervised learning of rare cases in autonomous vehicles

Thesis Title:

Sensor fusion for unsupervised learning of rare cases autonomous vehicles

Background:

Huawei is working on key components of L2-L3 autonomous driving platform and progressively shifting focus to development of breakthrough technologies required for L4-L5 autonomy. Tomorrow self-driving cars powered by AI will combine edge and cloud compute with vast number of sensors to safely and autonomously drive customers and deliver merchandise. At Huawei we develop a full-stack of technologies to enable this dream, including compute units, sensors, communication and cloud. We are seeking the best candidates for PhD CIFRE with a background in computer vision, deep learning, reinforcement learning, mapping, perception, sensor fusion, cognition and other related areas, to work as a part of IoV team in Paris Research Center (PRC). As a member IoV PRC you will closely work with multiple teams worldwide to grow your expertise and successfully transfer your research results into real products.

Research topic:

The core subject of this PhD should focus on solving the problem of sensor fusion for unsupervised learning of rare cases by leveraging vast amount of data available using multiple sensors and vehicles. By combining results of processing of the same physical entity by multiple redundant sensors and map data one could detect failures and root cause of it by comparing results among multiple sources. Unsupervised learning should further improve accuracy of finding errors especially in case of rare events, where training data for conventional sensors is absent. This data doesn’t have manual annotations, however automated SOTA methods could be used to extract valuable information about perception, localization, mapping to turn the problem into tractable. Unsupervised learning is considered to be among the most challenging problems as of today, therefore we expect to see tremendous progress in this area that could enable highly safe automated vehicles to become a part of our daily life.

Description of research activities:

  • Study state of the art on perception, sensor fusion and cognition
  • Study state of the art of supervised/unsupervised learning
  • Identify major bottlenecks in SOTA of (1 and 2) with application to self-driving car problems
  • Propose a new solution to one of the main bottlenecks (3) with focus on large scale practical application for self-driving cars
  • Research and develop algorithm based on the proposed solution (4) that could identify rare case failures of various sensors in unsupervised manner within focus of improving accuracy of sensor data for self-driving cars
  • Apply proposed algorithm (5) to the domain of self-driving cars using existing or specifically collected datasets
  • Publish research results in top conferences and participate to scientific seminars

Supervision:

This PhD will be supervised jointly between Huawei Technologies France and the Robotics Centre of Mines ParisTech and Armines

Prerequisites:

The candidate should be motivated to carry out world class research and should have a Master in Computer Vision and/or Robotics. He/She should have solid skills in the following domains:

  • Implement Code in Python & C++
  • Apply or use existing libraries for deep learning in project related tasks
  • Good knowledge in Git, ROS, OpenCV, Boost, multi-threading, CMake, Make and Linux systems
  • Code and algorithm documentation
  • Project reporting and planning
  • Writing of scientific publications and participation in conferences
  • Fluency in spoken and written English; French and/or Chinese is a plus
  • Intercultural and coordination skills, hands-on and can-do attitude
  • Interpersonal skills, team spirit and independent working style

Contact:

Interested candidates must send a detailed CV including their Master’s scores to dzmitry.tsishkou@huawei.com and bogdan.stanciulescu@mines-paristech.fr

Candidates must hold a working visa in France, or be nationals of one of the states of the European Union or the European Economic Area.

Deadline:
We aim to fill this position as soon as possible with the aim to commence in 2nd half 2019. Applications will be considered until a suitable candidate has been found.

Funding and location:
The PhD will be funded by a CIFRE contract and hosted in Paris area (Boulogne Billancourt and Paris), France.

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