Sky Route AI Mosebetsi wa Sehlooho: Drone ya Phano by Xilin Tang

Sky Route AI Mosebetsi wa Sehlooho: Drone ya Phano by Xilin Tang is a highly esteemed winner of the very prestigious 2025 Moputso oa Boronse oa A' Design Award in Moralo wa Bokamoso Competition Category.

BoronseBokamoso· 2025

Sky Route AI Mosebetsi wa Sehlooho: Drone ya Phano

by Xilin Tang

Client: Osrbot

Moputso oa Boronse oa A' Design Award Winner in Bokamoso Category

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The Design

About Sky Route AI Mosebetsi wa Sehlooho: Drone ya Phano

Mongolo wa Buka: Sky Route AI ke drone ya phano e etselitsweng ho romella dithoto maemong a mangata a ho ema tseleng e le nngwe ho isa qetellong ya leeto (last mile logistics). Dipaesele tse ngata di jarwa leetong le le leng, di tataisoa ke bohlale ba maiketsetso (artificial intelligence) bakeng sa moralo o phethahetseng wa tsela le ho fumana dithibelo ka nako ya nnete ka LiDAR le di-module tsa khamera. 'Mele wa yona o entswe ka carbon fiber composites, o bopuweng ka mokgwa wa CNC cutting le resin infusion, mme diarm tse mennang di dumella ho fofa dibakeng tse patisaneng tsa toropo. Diinjine tsa brushless di fana ka nako e ka isang metsotso e 45 ya ho fofa ka teshareto e le nngwe, hammoho le boima bo ka fihlang dikilograme tse 3. Sepheo ke ho fokotsa ditshenyehelo, ho khutsufatsa dinako tsa ho leta, le ho fokotsa tshollo ya khase e nang le kotsi ho tikoloho.

The Recognition

About the Moputso oa Boronse oa A' Design Award

Sky Route AI Mosebetsi wa Sehlooho: Drone ya Phano ke mohapi oa Moputso oa Boronse oa A' Design Award, kananelo e hlomphehang haholo e fuoang meralo e ikhethang e tsejoang ka boqapi, bohlale ba ho qapa le bohlale. Bahapi ba Boronse ke lintho tse nang le bokhoni ka ho felletseng le boqapi bo hlollang tse tiisang boiphihlelo bo bongata, mohopolo le bokhoni ba ho iphumana ba baqapi ba tsona. Sky Route AI Mosebetsi wa Sehlooho: Drone ya Phano e lebelletsoe ho ba ntho e hlomphuoang haholo, e ratoang le e ratehang, e nang le boprofeshenale bo bonahalang le mehopolo e mecha. Moralo ona o hapileng Moputso oa Boronse oa A' Design Award o kenyelletsa mekhoa e metle ka ho fetesisa bonong, mahlaleng, moralong le theknolojing mme o hlahella ka ho tsepamisa maikutlo lintlheng tse nyenyane. Sky Route AI Mosebetsi wa Sehlooho: Drone ya Phano e kutloisisa litlhoko hantle, e ama litakatso, e hapa maikutlo mme e tsosa takatso ea ho tseba.

Behind the Design

Press Kit

Credits, team members and technical details provided by the designer.

Unique Properties: This drone redefines last mile logistics by combining advanced AI with a carbon fiber body for repeated multi stop operations. Optimized to reduce flight time and emissions, it integrates real time obstacle detection and dynamic route planning. Its efficient multi takeoff capability lowers operational costs and ensures swift deliveries, distinguishing it from conventional single route drones. Additionally, advanced AI simulations accelerate development cycles for consistent and safe performance.
Dimensions & Packaging: Overall dimensions: 800 mm wide x 800 mm deep x 400 mm high, total weight approximately 3.5 kg. The carbon fiber chassis ensures a payload capacity of up to 3 kg. Brushless motors enable up to 45 minutes of flight time per charge. Integrated LiDAR and multi camera arrays provide real time obstacle detection, while modular battery packs facilitate efficient multi stop operations in various urban settings.
Tags: Drone, multi stop delivery, AI powered, carbon fiber, last mile logistics, eco friendly, cost efficient, advanced route planning, LiDAR, real time obstacle detection
Production Technology: Constructed from carbon fiber composites to maximize flight efficiency, the drone is realized through CNC cutting and resin infusion processes. AI driven simulation tools guide iterative refinements, optimizing aerodynamic performance and structural integrity. LiDAR and camera modules integrate seamlessly within modular housings, while brushless motors and a robust flight controller ensure high precision and reliability during multi stop missions.
Design Challenge: Integrating multi stop delivery AI with real time obstacle detection proved the toughest hurdle. Historically, drones had limited payload capacity; socially, public acceptance demanded robust safety features. Externally, evolving regulations demanded compliance, while scarce data and advanced materials constrained prototyping. Overcoming these obstacles shaped a reliable, efficient system.
Research: We conducted applied research aiming to cut delivery costs and boost reliability. Using iterative prototyping and AI simulations, we collected flight and route data with sensor arrays. Test flights with volunteers showed multi package deliveries reduced wait times by 30%. This insight informed safer navigation, driving business efficiency, easing urban congestion, and inspiring new drone design standards.
Inspiration: Inspired by the global need for more flexible, cost efficient, and eco friendly logistics, we harnessed advanced AI simulations to refine multi stop capabilities in a carbon fiber drone. Rising labor costs and congested roads highlighted the urgency to innovate last mile delivery, so our research focused on optimizing flight performance, payload handling, and dynamic route planning.
Project Duration: The project started in October 2024 in Auburn, Alabama, USA, and ended in January 2025 in Auburn, Alabama, USA.
Operation Flow: SkyRoute AI is operated via a user friendly app or controller. After takeoff, it can fold or unfold its arms to carry multiple packages, navigate narrow urban spaces, and revert to a stable form. With real time obstacle detection and dynamic route updates, it delivers multiple packages to different locations in a single run. This flexible, efficient approach reduces wait times, lowers costs, and outperforms traditional drones in speed and reliability.
Image Credits: Image #1: Designer XilinTang, Auburn, 2024
Image #2: Designer XilinTang, Auburn, 2024
Image #3: Designer XilinTang, Auburn, 2024
Image #4: Designer XilinTang, Auburn, 2024
Image #5: Designer XilinTang, Auburn, 2024