Autonomous battery swap system for 10-kg cargo UAVs utilising ground stations

Project Summary

The project aims to conduct a feasibility study that delves into the obstacles of implementing autonomous parcel dispatch using delivery and cargo UAVs. The study will identify the optimal solution and produce a computer prototype design (TRL 2 to 4). To meet the standards set by the DAL-B aerospace guidelines, the system must be exceedingly dependable with a failure probability of less than one in every 10 million. The ultimate goal is to create a reliable and effective system for autonomous parcel dispatch, ensuring that deliveries can be made efficiently and safely.

Project Achievements

Focus: The project primarily aimed to automate and optimize drone logistics in two key areas: autonomous battery swapping and automated parcel dispatch. The objective was to meet DAL-B aerospace standards, enhancing drone endurance and operational efficiency. Main Achievements: • Successfully developed and lab-tested a prototype for automated battery swapping thatmeets stringentaerospace standards. • Implemented an autonomous parcel dispatch system to streamline logistics and parcel handling. Programme Highlights: • Collaboration with The National Robotarium provided access to a highly skilled talent pool,driving innovation and quality.

Conclusions

The projects successfully proved the feasibility of autonomous battery swapping and parcel dispatch for UAVs, meeting DAL-B aerospace standards. In collaboration with The National Robotarium, we produced feasibility reports and preliminary designs, advancing our aims. We also discovered value in optimising for modular UAV compatibility. The success attracted additional private investment, validating the project’s viability and future potential.

Next Steps

The next step is live testing, supported by our recent application to the Connected Places Catapult accelerator and signed LOIs with UK logistics providers for commercial trials. We’re actively seeking additional funding from private investors, who’ve shown increased interest thanks to TRIG’s foundational R&D support. The TRIG programme significantly accelerated our project’s journey towards commercialisation and helped attract otherwise risk-averse investors to our hardware start-up. • Achieved pinpoint landing accuracy and incorporated weather-resistant structures,thereby elevating the system’s efficiencyand reliability. • Introduced AI-driven automated drone inspection to minimize downtime and improve operational performance. Activities Undertaken: • Extensive R&D for system design and AI integration. • Collaborative brainstorming to tackle technical and business constraints. • Feasibility reports and computer models to validate the approach and inform future development.