You take on navigation challenges for autonomous mobile robots in a variety of industrial settings. You broaden the possibilities for the future applications.
Flanders Make researchers are creating demonstrators with next generation navigation algorithms that are adaptable and self-learning. An increasing number of autonomous functionalities could be added to industrial autonomous robots. While the industry hesitates, Flanders Make proves that these technologies are easy to deploy in complex settings and more robust when needed, eg. in busy or noisy industrial contexts.
Object identification, localization, path planning & obstacle avoidance
As an expert or young potential in navigation algorithms for autonomous mobile robots, drones and vehicles
- you work together in a team which combines expertise in sensing, computer vision, odometry, signal processing, adaptive & learning control, embedded software, robotics, machine learning and artificial intelligence;
- with the team you solve challenges in sensor fusion & simultaneous localization and mapping (SLAM), static & dynamic world modelling, optimal and real-time path planning, motion planning and motion control, where you focus on indoor localization, world modelling and context adaptive path planning.
For a variety of industrial cases (small indoor pick- and place drones & robots in warehouses, assembly cobots, large outdoor or heavy-weight forklifts) you will
- Write 2D/3D navigation algorithms for indoor/outdoor localization, path planning & tracking, object identification and obstacle detection & avoidance;
- Ensure innovation by improvements to simultaneous localisation and mapping (SLAM), advanced filtering and sensor fusion (Kalman filtering, numeric optimization,… ) and radically enhance the visual perception & localization. You add & improve items using python, Matlab or C++ and work in environments like ROS on the selected sensor set (Vision, LIDAR, UWB, IMU, …);
- Simulate all the functionalities and validate your result on a mobile robot and drone demonstrator;
- Experienced engineers will also trace and present industrial challenges and research opportunities or coach young engineers and lead projects.
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