The ideal candidate should have substantial experience designing navigation systems for autonomous platforms operating in indoor environments.
This includes expertise in at least one of the following areas : sensor calibration, object detection, simultaneous localization and mapping, path planning, and low-
level controller design. They should take ownership of their work, be self-motivated & practical in their problem-solving and thrive in a fast-
paced, highly collaborative applied research environment.
balance calibration of both standard and fisheye cameras, Time-of-Flight cameras, Lidar, IMU, Odometry
Experience with commonly used packages such as OpenCV, PCL, ROS, Gazebo Good high-level understanding of autonomous navigation systems and algorithms including SLAM, Localization, Obstacle Detection and Tracking Passionate about learning new algorithms in different components of autonomous navigation system and improving existing implementation of algorithms
Experience working with graph optimization backends for a SLAM solution (GTSAM, g2o, CERES) (Preferred) knowledge in GPU programming, GPGPU programming, Linux architecture and GPGPU acceleration (preferred) publications in top robotics conferences (ICRA, IROS, etc.) (preferred)
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