A pioneering medical device company is seeking a Sensor Fusion Engineer Intern for a 3-month internship in Hayward, California, with potential for full-time conversion. Ideal candidates are undergraduate or graduate students with a strong foundation in robotics, computer vision, estimation theory, and signal processing. Responsibilities include developing algorithms to combine IMU data and camera images for enhanced localization within the PillBot™, along with collaborating with other interns to ensure effective robot localization. Competitive opportunity to gain hands-on experience in a multidisciplinary team.
Qualifications
Strong academic background in estimation theory, signal processing, and control systems.
Experience with Kalman filters or similar probabilistic state estimation techniques.
Familiarity with computer vision concepts and processing camera data for pose estimation.
Responsibilities
Design and implement algorithms to combine IMU data with visual information.
Apply Kalman filters to estimate the robot's position and orientation.
Utilize camera images for visual odometry to correct IMU drift.
Test and validate the sensor fusion system's accuracy and robustness.
Work with Machine Learning/Computer Vision intern to ensure complementary approaches.
Skills
Estimation theory
Signal processing
Computer vision
Kalman filters (EKF, UKF)
Python
C++
Education
Pursuing or completed a degree in Robotics, Electrical Engineering, or Computer Science
Job description
A pioneering medical device company is seeking a Sensor Fusion Engineer Intern for a 3-month internship in Hayward, California, with potential for full-time conversion. Ideal candidates are undergraduate or graduate students with a strong foundation in robotics, computer vision, estimation theory, and signal processing. Responsibilities include developing algorithms to combine IMU data and camera images for enhanced localization within the PillBot™, along with collaborating with other interns to ensure effective robot localization. Competitive opportunity to gain hands-on experience in a multidisciplinary team.