Utility Robot Fleet Dispatch for Short-Distance Autonomous Delivery

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Solution Overview

Problem

Existing systems fail to efficiently accommodate short-distance delivery services, particularly for utility robots, and lack the capability for both autonomous and semi-autonomous operation while ensuring economic delivery of goods.

Innovation Solution

A fleet network of utility robots, including trucks and self-driving cars, communicates seamlessly to share navigation data and utility requirements, enabling autonomous or semi-autonomous operation with sensors for localization, obstacle detection, and route planning, and includes storage compartments for secure delivery of items like pharmaceuticals and food.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If a fleet network with multiple utility robots is implemented, then delivery efficiency and coverage are improved, but system complexity and coordination requirements increase

Engineering Contradiction:
Improvedelivery efficiencyVSAvoidsystem complexity
Core Design Contradiction:
ProductivityVSDevice complexity

Solution Approach 1:

The fleet network is segmented into autonomous utility robots that operate independently but coordinate through a communication network. Each robot functions as an independent unit with its own sensors, processors, and execution capabilities, allowing the system to scale without proportionally increasing central control complexity.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

Utility robots are designed as multi-functional units capable of performing various delivery tasks across different environments. The standardized robot design with adaptable sensor configurations and route planning algorithms allows a single platform to serve multiple delivery scenarios, reducing overall system complexity.

Inventive Principle:
Principle #6Universality (Multi-functionality)

2Extent of automation

If autonomous operation is implemented, then operational costs are reduced, but reliability and safety requirements increase

Engineering Contradiction:
Improveautonomous operationVSAvoidsafety
Core Design Contradiction:
Extent of automationVSReliability

Solution Approach 1:

The utility robot performs self-service through autonomous navigation, obstacle detection, and route planning without human intervention. The robot independently processes sensor data, makes navigation decisions, and executes delivery tasks, reducing operational costs while maintaining safety through multiple redundant sensing systems and real-time environmental monitoring.

Inventive Principle:
Principle #25Self-service

Solution Approach 2:

The autonomous system incorporates continuous feedback loops where sensors monitor the environment, the processor analyzes data, and the robot adjusts its behavior in real-time. This feedback mechanism ensures safety by detecting obstacles, adapting to changing conditions, and maintaining reliable operation throughout the delivery process.

Inventive Principle:
Principle #23Feedback

3Measurement precision

If sensors and obstacle detection systems are added, then navigation accuracy and safety are improved, but device complexity and cost increase

Engineering Contradiction:
Improvelocalization accuracyVSAvoidsensor complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The sensor system is configured with local quality by selecting and positioning specific sensors based on the robot's operational context and environment. Different sensor types and configurations are applied to different locations on the robot, optimizing measurement precision for navigation and obstacle detection while avoiding unnecessary sensor complexity.

Inventive Principle:
Principle #3Local quality

4Adaptability or versatility

If the utility robot can navigate complex urban environments with obstacles, then delivery coverage is improved, but navigation complexity and computation requirements increase

Engineering Contradiction:
Improveenvironmental adaptabilityVSAvoidnavigation complexity
Core Design Contradiction:
Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The navigation system employs dynamic route planning that adapts to changing environmental conditions in real-time. The processor continuously updates the navigation path based on sensor input, obstacle detection, and fleet network information, allowing the robot to navigate complex urban environments with varying obstacles, pedestrians, and traffic conditions without requiring overly complex pre-programmed navigation logic.

Inventive Principle:
Principle #15Dynamics

Data Source

PatentEP3803736B1System and method for distributed utility service execution
Publication Date: 2025.11.12 DEKA PRODUCTS LP
  • EP3803736B1 patent drawingFigure 1
  • EP3803736B1 patent drawingFigure 2
  • EP3803736B1 patent drawingFigure 3

AI summary

Utility services related to executing services requiring trips of various lengths, and short-distance assistance to customers. Utility services can be delivered by semi-autonomous and autonomous vehicles on various types of routes, and can be delivered economically. A network of utility vehicles provide the utility services, and can include a commonly- shared dispatch system.