Scout Drone Delivery Point Assessment for Multiple Drone Systems
Solution Overview
Problem
Current drone delivery systems face inefficiencies due to limited payload capacity and range, as well as challenges in navigating obstructions and environmental conditions at delivery points, leading to delayed or canceled deliveries and potential product damage.
Innovation Solution
Implementing a system where scout drones scan delivery points to assess conditions, determining suitability for delivery, and allowing delivery drones to either proceed with delivery, reschedule, or choose alternative drop areas based on the assessment, using video imaging, sensors, and communication equipment to inform customers of issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If drones are used for delivery, then delivery speed and efficiency are improved, but limited payload capacity and range reduce delivery capability
Solution Approach 1:
The delivery system is divided into multiple independent drones, each with limited payload capacity. Instead of requiring a single large-capacity drone, the system segments the delivery fleet into multiple units that can operate independently or in coordination, thereby maintaining high productivity while accepting the payload limitations of individual drones.
2Speed
If drones deliver directly to delivery points, then delivery speed is improved, but obstructions and environmental conditions cause delays and cancellations
Solution Approach 1:
The system performs preliminary scanning of the delivery point using a second drone before the actual delivery occurs. This preliminary action identifies potential obstructions or environmental issues in advance, allowing the system to select alternative delivery points or prepare mitigation strategies, thereby maintaining delivery speed while improving reliability.
Solution Approach 2:
The system implements a feedback mechanism where the scanning drone provides real-time information about delivery point conditions to the control system. Based on this feedback, the system can dynamically adjust delivery routes, select alternative drop areas, or reschedule deliveries, ensuring reliable delivery execution while maintaining overall speed efficiency.
3Loss of time
If drones leave products in drop areas, then delivery is completed quickly, but environmental conditions may damage products
Solution Approach 1:
The system performs preliminary environmental assessment of the drop area using the scanning drone before the delivery drone releases the product. This preliminary action identifies harmful environmental conditions such as water presence or obstructions, allowing the system to select safe delivery locations and complete the delivery quickly without exposing products to damage risks.
Solution Approach 2:
The scanning drone acts as an intermediary between the delivery drone and the delivery point. It assesses environmental conditions and communicates safe or unsafe status to the control system, which then directs the delivery drone to appropriate locations. This intermediary function enables rapid delivery while filtering out harmful environmental factors that could damage products.
Data Source
AI summary
Embodiments for delivering goods to customers by a processor are described. An item is selected to be delivered to a delivery point. The selected item is loaded onto a first drone. The delivery point is scanned with a second drone. Based on the scanning of the delivery point, the delivery point is determined to be in a first condition or a second condition. If the delivery point is in the first condition, the first drone delivers the selected item to the delivery point.