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Robotics Engineer - SLAM
Navigation and Planning
Hybrid in London
Up to £100k
The role involves designing, implementing, and optimizing SLAM (Simultaneous Localization and Mapping) algorithms for real-time localization and mapping in robotics.
Key responsibilities include integrating data from multiple sensors for improved accuracy, developing localization and mapping algorithms, and calibrating sensors.
The role also focuses on optimizing SLAM for real-time performance on embedded systems, collaborating with robotics teams for navigation integration, and validating SLAM systems through testing.
Additionally, it involves staying current with research developments and contributing to innovation in SLAM and robotics.
Requirements:
- Deep knowledge of SLAM techniques, including feature-based, visual, and LiDAR, with experience in implementing and customizing these algorithms for specific robotic tasks.
- Skilled in sensor fusion, integrating data from cameras, LiDAR, IMUs, and odometry to enhance localization and mapping accuracy.
- Proficient in C++, Python, or MATLAB, with experience in developing, debugging, and optimizing robotics software.
- Understanding of robotic navigation, including path planning and obstacle avoidance, with experience integrating SLAM into navigation systems.
- Experienced in sensor calibration for cameras and LiDAR, ensuring precise measurements and data fusion.
- Familiar with embedded systems and hardware integration, optimizing SLAM for resource-constrained platforms.
- Experienced with robotics simulation tools like Gazebo or ROS, and conducting simulation-based testing of SLAM systems.
- Strong problem-solving and analytical skills for addressing complex mapping and localisation challenges and improving SLAM performance.
Think you'll be a good fit? Apply now for consideration!
