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

Moralo oa Sky Route AI Mosebetsi wa Sehlooho: Drone ya Phano ka Xilin Tang ke mohlodi oa khau e hlomphehang haholo ya 2025 Moputso oa Boronse oa A' Design Award Mokhahleong oa Tlhodisano oa Moralo wa Bokamoso.

BoronseBokamoso· 2025

Sky Route AI Mosebetsi wa Sehlooho: Drone ya Phano

ka Xilin Tang

Moreki: Osrbot

Mohlodi oa Moputso oa Boronse oa A' Design Award Mokhahleong oa Bokamoso

139,713

Mohlodi oa Khau ea Netefaditsweng

Netefatsa Boemo ba Khau bakeng sa #171188

Sheba ho A' Design Award Tokollo ya Boraditaba Baeche ya Moputso

Mebala

Moralo

Mabapi le 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.

Kamohelo

Mabapi le 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.

Ka Mora Moralo

Sete ya Boraditaba

Litlhaku, ditho tsa sehlopha le lintlha tsa botekgeniki tse fanoeng ke moetsi wa moralo.

Boleng bo Ikhethang: 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.
Boholo le Phuthelo: 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.
Lithegi: Drone, multi stop delivery, AI powered, carbon fiber, last mile logistics, eco friendly, cost efficient, advanced route planning, LiDAR, real time obstacle detection
Theknoloji ya Tlhahiso: 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.
Phephetso ya Moralo: 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.
Dipatlisiso: 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.
Kgothaletso: 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.
Nako ya Projeke: The project started in October 2024 in Auburn, Alabama, USA, and ended in January 2025 in Auburn, Alabama, USA.
Tsamaiso ya Mosebetsi: 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.
Litlotla tsa Setshwantsho: 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