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background in robotics, control engineering, sensor fusion, dynamic modelling, and real-time control. Experience with mobile robots (wheeled/ground and/or aerial), including aspects of locomotion, dynamics
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from data from a multimodal sensor. Merging data from multimodal sensors located in different spatial positions: calibration and synchronization. Transforming fused data: sensor fusion and feature fusion
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system ROS/ROS2, PX4, LiDAR, Stereo and Monocular vision, Perception, AI, ML, Path Planning Control, Sensor Fusion Algorithms;; - Previous experience in Deep Learning with LiDAR and vision systems
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Position Overview School / Campus / College: College of the Environment Organization: Earth and Space Science Title: Postdoctoral Scholar in Multi-Hazard, Multi-Sensor Monitoring at Mt Rainier
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technologies to push the frontier of plasma performance. Engineering radiation-hardened robotics and sensor systems for remote maintenance and reliable fusion operations. Artificial Intelligence Developing
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of sensor fusion (LIDAR, vision, IMU, GPS, etc.). Teamwork skills, technical curiosity, and a proactive mindset. Specific Requirements Valuable extras Previous experience in autonomous navigation or SLAM
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, multi sensorial fusion and multirobot coordination, including multirobot perception, decentralization and mission execution. The RAI team has a strong European and National participation in multiple R&D&I
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), or biological sensors (sweating, ECG, etc.). These scenarios raise new scientific challenges, both in terms of modeling (intermodal alignment, joint representation, generation control) and in terms of usage
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GNC sensors and actuators; Autonomous Navigation systems including data fusion, vision-based navigation and hybrid navigation concepts, guidance & optimisation techniques, including artificial
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. Neuromorphic fusion of co-localized visual sensors Fusing different sensory modalities is a powerful mechanism to extract information about a perceived environment: throughout our lives, we hear with our eyes