RESEARCH ENGINEER POSITION AVAILABLEROS & path planning for drones

Duration: 1 year
Employer: University of Haute Alsace
Location: IRIMAS laboratory, Mulhouse, France
Salary: ANR funding (may vary according to experience)Supervisors: L. Idoumghar, J. Lepagnot & L. Jourdan

1. Context
This research engineer position is part of a joint French–German research project on future
security in urban areas, funded by the French National Research Agency (ANR) and theGerman Federal Ministry of Education and Research (BMBF), from 2017 to 2020. This projectis entitled “Organized Pedestrian Movement in Public Spaces: Preparation and Crisis
Management of Urban Parades and Demonstration Marches with High Conflict Potential”(OPMoPS). The main outcome of this project will be a decision support tool based onmathematical, computer science and sociological research, which will help the forces of civil
security (FCS) to prepare and control urban parades and demonstration marches (UPM), todetect risk situations, and to react to possible threats to individuals and civil security fast andefficiently.
In this context, the IRIMAS institute coordinates the work of the French involved partners andleads an optimization work package devoted to solve the following research problems: findgood locations for security personnel before and during the UPM, roster plans for security
personnel, evaluate suggested and recommend good UPM routes, placement of cameras anddrones with automatic detection of main hazardous situations.
The selected candidate will join the IRIMAS optimization group involved in OPMoPS, in order
to assist them in the tasks related to automatic path planning of drones. The research works
conducted by this group on these tasks have already led to several publications [1, 2, 3].
2. Mission
As a research engineer, your role will be to assist this group in the following possible tasks:developing simulations of quadcopter/quadrotor in outdoor/urban environments, inorder to avoid obstacles, using robotic platforms (ROS (Robot Operating System,https://www.ros.org), V-Rep, etc.);modelling and integrating real-world test cases into the robotic platform for thesesimulations;performing experimental studies, then gathering and analyzing the results;
developing tools to easily create, handle and display test cases and results.
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3. Required skills and background
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The candidates must have a Master degree or equivalent in computer science orapplied mathematics.
The candidates should have, ideally, a strong experience with ROS, Gazebo, MoveIt,rqt, RVIZ.
Experience importing street views from Open Street Maps/Google Maps to use as aGazebo world file.
Strong Python and C++ coding skills.
Familiarity with sensors, such as LIDAR, IMU, GPS, radar, or cameras relevant to drone.
Hands on experience in design and development of autonomous vehicle/robot
modules (like object detection/tracking, localization and navigation, path planning,
behavioral planning, SLAM, control system (position, velocity, force control, etc.)).
The candidates must be fluent in English.

4. Application
To apply to this position, please send to lhassane.idoumghar@uha.fr, julien.lepagnot@uha.fr:
CV, motivation letter, copy of Master degree, transcript of grades from last two years ofstudy, 2-3 recommendation letters, name and contact information of at least one previous
supervisor or teacher that can support your application.
5. References[1] Ghambari S., Lepagnot J., Jourdan L. & Idoumghar L. (2018), “A comparative study ofmeta-heuristic algorithms for solving UAV path planning”. IEEE-Symposium Series on
Computational Intelligence (SSCI) 2018, Bangalore, India, November 2018.
[2] Ghambari S., Idoumghar L., Jourdan L. & Lepagnot J. (2019), “A* based differential
evolution algorithm for UAV path planning problem in urban environment”. Artificial
Evolution, Mulhouse, France, October 2019.
[3] Ghambari S., Idoumghar L., Jourdan L. & Lepagnot J. (2019), “An improved TLBO
algorithm for solving UAV path planning problem”. IEEE-Symposium Series on
Computational Intelligence (SSCI) 2018, Xiamen, China, December 2019.

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