Reference : UPR8001-VIVCAD-002
Workplace : TOULOUSE
Date of publication : Thursday, July 21, 2022
Type of Contract : FTC Technical / Administrative
Contract Period : 15 months
Expected date of employment : 1 November 2022
Proportion of work : Full time
Remuneration : 2548€ (gross salary)
Desired level of education : Engineer
Experience required : 1 to 4 years
The hired engineer will be in charge of the implementation and the integration of the control and vision algorithms on the available mobile robot. He/she will be involved in the design, the evaluation and the validation of these algorithms, both in simulation and through experimental campaigns either in the laboratory or in commercial orchards located near Toulouse. He/she will have to participate to the project management, the scientific results dissemination and the supervision of internship students recruited in the project.
- C/C++/Python programming
- Implementation of vision and control algorithms using ROS
- Participation to the experimental campaigns in LAAS and in commercial orchards
- Participation to the project management (documentation, organisation, tests, formal oral presentations...) and to the results dissemination
- Internship students supervision
- Engineer in robotics or in vision or in computer science
- Expected mandatory technical skills : excellent skills in Python and C++, very good skills in ROS-Gazebo and vision and perception tools (Opencv, PCL, etc.)
- If possible: good skills in control theory and/or learning methods for vision
- Excellent skills in oral and written communication in English and in French
- Autonomy, team working
The work is part of the ANR French/Brazil project ARPON (Autonomous Robotic Platform for Orchard Navigation). It involves two partners : the LAAS-CNRS (and the Robotics, Action, Perception Team) on the one hand and the UFPE (University of the Pernambuco State, Recife, Brazil) with the CIn (centro de informatica) on the other hand. This project aims at developing a navigation system allowing a mobile robot to autonomously move in an orchard. As the GPS signal is not always available due to the fruit trees canopy, the developed navigation strategies only rely on embedded sensors (mainly RGB-D cameras, laser). A proof of concept is expected at the end of the project. Experimental campaigns will then be regularly organized in commercial orchards located near Toulouse.
The recruited engineer will join the RAP team from LAAS-CNRS. He/she will work in close collaboration with the PhD student in charge of the control algorithms. He/she will also collaborate with the permanent staff involved in the project to participate to its management and to the hired internship students supervision.
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