A method is presented to synchronize and aid the absolute navigation solutions of the members of a swarm by means of relative inter-swarm measurements. Moreover, the operational benefits thereof are discussed.

Collaborative operation of vehicles, especially of unmanned aerial vehicles in close formation, requires accurate relative and absolute navigation. A novel method for collaborative multi-sensors fusion of relative and absolute navigation information is presented designed to cope with GNSS-denied environment.

Relative inter-swarm measurements and absolute navigation means cannot be fused straight away as they are defined in fundamental different frames. Moreover, the sensor fusion has to fulfill two objectives – firstly, restoring the relative geometry of the swarm, and secondly, determining the absolute positions of each vehicle in an optimal way for the overall swarm.

Key for collaborative navigation is to establish a common knowledge within the swarm which is achieved by exchanging the absolute state estimations, the state uncertainties and the relative measurements. Based on the common knowledge the “Consistent INS Drift Algorithm” computes for each vehicle a new position which is statistically optimal for the overall swarm. Simultaneously, these new positions represent the actual geometry of the swarm by essentially resampling the relative measurements. By fusing these new positions the navigation filters are synchronized and the relative measurements are implicitly used to aid the absolute navigation solutions.

This reveals several operational benefits: the absolute navigation solutions are consistent – the whole swarm drifts consistently as only the Inertial Navigation Systems (INS) may remain as absolute navigation means, and hence, the naming “Consistent INS Drift Algorithm”. Moreover, the drift is statistically slower than the best individual INS. Having at least one vehicle equipped with a drift-free navigation mean such as Terrain Referenced Navigation stops the swarm to drift. Therefore, heterogeneous navigation systems are natively supported enabling true collaboration.

Collaborative Navigation - Synchronizing and Aiding the Absolute Navigation of Swarm Members using Relative Inter-swarm Navigation Information

***Session Chair: Andy Proctor***<br>
***Session Co-Chair: Peter Soar***



Session 1.4.

technical paper

### Welcome to Navigation 2021!

Our aim was to bring diverse disciplines together to stimulate insights and knowledge sharing towards a more navigable world. We hope we achieved this!

Navigation and timing are critical to the world we all inhabit. We believe that the work of the wider navigation community enables societal benefit including support to national grand challenges and also the United Nations’ Sustainable Development Goals. To achieve this requires collaboration and understanding across science, technology and practice.

Navigation 2021 is about much more than technology innovation, it also showcases science and research from across the wider community, including animal navigation, cognition and human factors.


Navigation 2021

Our aim was to bring diverse disciplines together to stimulate insights and knowledge sharing towards a more navigable world. We hope we achieved this!

Tobias Neuhauser

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Collaborative Navigation - Synchronizing and Aiding the Absolute Navigation of Swarm Members using Relative Inter-swarm Navigation Information

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