Decentralized Drone Docking Assignment for Last-Mile Delivery

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Solution Overview

Problem

Last-mile delivery using unmanned aerial vehicles (UAVs) faces challenges due to the mobility of delivery vehicles and limited operational range, making it difficult for UAVs to return to their launch platforms, especially in scenarios with multiple vehicles and fleets operating remotely.

Innovation Solution

A decentralized drone-to-station assignment system where UAVs can autonomously select a docking station by broadcasting their status and receiving priority-based responses from nearby vehicles or fixed stations, allowing them to choose the most suitable location for recharging and returning, even in the absence of a backhaul connection.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Area of stationary object

If UAVs are assigned to distinct delivery routes remotely from one another, then delivery coverage is expanded, but the difficulty of UAVs returning to the delivery vehicle increases

Engineering Contradiction:
Improvedelivery coverage areaVSAvoidUAV return to delivery vehicle
Core Design Contradiction:
Area of stationary objectVSEase of operation

Solution Approach 1:

The system segments the delivery network into multiple independent delivery vehicles, each with its own fleet of UAVs. Each UAV is assigned to a specific delivery vehicle and maintains a dedicated return route, enabling independent operation and simplifying the return process while expanding overall delivery coverage across remote areas.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The system introduces intermediate docking stations as mediators between UAVs and delivery vehicles. These stations serve as designated meeting points where UAVs can return to their delivery vehicles, facilitating the return process in remote locations where direct visibility or communication may be limited.

Inventive Principle:
Principle #24Intermediary (Mediator)

2Productivity

If multiple delivery vehicles and fleets of UAVs operate in the same region, then delivery capacity is increased, but the complexity of fleet management increases

Engineering Contradiction:
Improvedelivery capacityVSAvoidfleet management complexity
Core Design Contradiction:
ProductivityVSDevice complexity

Solution Approach 1:

The fleet management system segments control into vehicle-level autonomous managers, with each delivery vehicle independently managing its own UAV fleet. This segmentation reduces central management complexity while enabling coordinated operation across multiple vehicles through standardized communication protocols and priority-based routing algorithms.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

Each delivery vehicle is equipped with autonomous fleet management capabilities, allowing it to independently dispatch, track, and retrieve UAVs from its fleet. The vehicles self-coordinate with each other through priority-based communication, eliminating the need for complex centralized control while maintaining high delivery capacity across multiple regions.

Inventive Principle:
Principle #25Self-service

3Use of energy by moving object

If UAVs operate with limited operational range, then energy consumption is reduced, but the difficulty of returning to the delivery vehicle increases

Engineering Contradiction:
ImproveUAV energy consumptionVSAvoidUAV return to delivery vehicle
Core Design Contradiction:
Use of energy by moving objectVSEase of operation

Solution Approach 1:

The system performs preliminary actions by pre-calculating optimal return routes and pre-positioning docking stations within UAV operational range. The autonomous fleet managers anticipate return needs and proactively establish communication links and docking protocols before UAVs need to return, ensuring smooth returns within energy constraints.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The system dynamically adjusts UAV operational parameters including range, altitude, and routing based on real-time conditions. The autonomous managers continuously optimize flight paths and return protocols to match current energy levels and environmental conditions, enabling reliable returns while minimizing energy consumption through adaptive rather than fixed operational parameters.

Inventive Principle:
Principle #15Dynamics

Data Source

PatentUS11783274B2Systems and methods for a decentralized hybrid air-ground autonomous last-mile goods delivery
Publication Date: 2023.10.10 FORD GLOBAL TECH LLC
  • US11783274B2 patent drawing
  • US11783274B2 patent drawing
  • US11783274B2 patent drawing

AI summary

System and methods for a decentralized hybrid air-ground autonomous last-mile goods delivery are disclosed herein. A drone can include a controller configured to cause the drone to depart from a docking station of a vehicle, transmit a discovery message to available vehicles in an operating area, the discovery message having drone metadata, select at least one of one of the available vehicles based on response codes received from the available vehicle, or a nearest fixed docking station, and dock with a docking station of the one of the available vehicles or the nearest fixed docking station.