Something old, something new…dead reckoning, IMUs, and autonomous navigation

KVH inertial systems provide critical data for May Mobility's autonomous navigation solution

As the technical challenges of autonomous navigation continue to keep some of the best engineering minds up at night, May Mobility, a small autonomous vehicle company from Michigan, launched the first commercial deployment of autonomous vehicles in the United States in June 2018.

KVH, 1725 IMU, Inertial Measurement Unit, autonomous navigation
The KVH 1725 IMU is a 6-degrees-of-freedom (6-DOF) sensor that delivers the high performance and stability of KVH’s fiber optic gyros (FOGs) affordably for diverse applications, including autonomous navigation.

How did May Mobility beat others to this milestone? While the big names in autonomous vehicles are working on artificial intelligence and deep learning algorithms for their autonomous navigation solutions, the engineers of May Mobility chose to apply existing navigational tools to develop an innovative localization solution for the company’s electric shuttles. Instead of artificial intelligence and deep learning, the navigation system on May Mobility’s autonomous shuttles relies on highly accurate dead reckoning and odometry as well as some precision sensing from KVH’s 1725 inertial measurement unit (IMU).

Dead reckoning and odometry are not new navigational techniques. Dead reckoning allows you to calculate your current position by using a previously determined position based on known or estimated speeds over time and course.

Columbus and most mariners of the Age of Exploration relied on dead reckoning to navigate using simple but reliable tools to track compass heading, speed, and time spent on each heading and at each speed. The more modern technique of odometry uses data from motion sensors to estimate change in position over time and to estimate position relative to a starting location.

However, odometry is sensitive to errors due to the integration of velocity measurements over time to give position estimates. Rapid and accurate data collection, instrument calibration and processing are necessary for odometry to be used effectively.

Autonomous vehicles require extremely precise localization using either the data from onboard sensors to determine a change in position over time, or odometry observations of the environment and accurate identification of obstacles in its path. That data is delivered via sensors including radar, Lidar, GPS, and cameras. Put another way, good dead reckoning is vital for the centimeter-level localization required for autonomous navigation in urban environments.

The urban, low-speed operating environment of May Mobility’s electric vehicles made the combination of dead reckoning and odometry ideal for this autonomous navigation system. A crucial component was a highly accurate inertial system that was also competitively priced. May Mobility found its answer in KVH’s 1725 IMU.

KVH, May Mobility, 1725 IMU, autonomous navigation, case studyDownload the case study about May Mobility’s unique autonomous navigation solution today


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About Pam Cleveland 29 Articles
Manager, Inertial Navigation Marketing and Global Proposals