07 Dec 2021

Northstar: Map the Gap Insight

Autonomous control of an amphibious bottom-crawler – navigating on land and subsurface

tpgroup is applying its experience in fully-autonomous control of land and surface platforms to a new, amphibious bottom-crawler, purpose-built for remote reconnaissance and surveying.

This work is for Phase II of the Map the Gap Challenge that focusses on applying autonomy to help the military cross rivers, streams and canals. tpgroup is part of an industry group, led by Digital Concepts Engineering (DCE), that successfully won a contract within this Phase.

Image: Contains public sector information licensed under the Open Government Licence v3.0.

Removing risk from reconnaissance

Suitable crossing points across obstacles, such as rivers and streams, need to be considered and selected to ensure the safe passage of military units

Currently specialist engineers are deployed to inspect both banks of the river with divers used to inspect the river bed to determine appropriate entry and exit sites. This approach, sometimes using rudimentary kit like row boats and string, can be time consuming and leaves ground forces vulnerable to attack. The recce engineers themselves are also exposed to greater risk during the survey from both the enemy and the unknown environment they face.

The use of autonomy removes personnel from this risky exercise, allowing them to remain a distance away from the wet gap and deploy a platform that reaches the entry point and performs the subsurface reconnaissance – without human intervention. This innovative technology can reduce the burden on the user whilst increasing the safety and speed of operations.

Please click here for full scope on the Map the Gap Competition

Northstar’s sensor-agnostic GNSS-denied autonomy

Common SLAM pipeline developed for Northstar

Northstar has been designed to work with different sensors and sensor types to continue operation even in the most restricted environments. It fuses sensor and odometry* data to detect dynamic obstacles and determine how the platform is moving through an unknown environment.

A common Simultaneous Localisation And Mapping (SLAM)* digital pipeline has been developed as part of Northstar which concurrently constructs and updates a map whilst also tracking the platform’s location within the map. With a single digital pipeline, Northstar can interface with a variety of sensors to provide an optimised solution for a diverse range of multi-domain use-cases, such as moving the platform between land and water.

How does this work in practice? For the Map the Gap project’s amphibious unmanned ground vehicle (UGV), tpgroup is developing LiDAR* for collision avoidance to enable the platform’s mission from the rendezvous site to the river. To then traverse underwater, Northstar switches to using sonar to avoid any obstacles encountered on the river bed. As a sensor-agnostic software, these data can both be used on one instance of Northstar to offer autonomous control in this complex scenario.

Project Progress & developments

This Map the Gap Challenge Phase II project brings together a number of integrators and suppliers to ultimately exhibit an end-to-end system at a two-week long Technical Readiness Level (TRL) 6 demonstration to the British Army in early 2022.

With an existing autonomous land capability, tpgroup is extending Northstar subsurface to ensure safe routing and obstacle avoidance underwater for this project. Considerable progress has been made since the start of the contract with simulation work carried out and testing locally on a prototype autonomous platform. Currently trials are underway integrating Northstar with the UGV on both land and underwater. The trials take place over a number of weeks alongside hardware integration tests with the other collaborators.

*Terms of reference:

  • Odometry: The use of data from motion sensors to estimate change in position relative to a starting location.
  • SLAM: (simultaneous localisation and mapping) is a method that enables the building of a map and the localisation of a platform in that map at the same time. SLAM algorithms allow the platform to navigate and map unknown environments.
  • LIDAR: A method for determining distance or range by targeting an object with a laser and measuring the time for the reflected light to return to the receiver.

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