Modular Autonomous Delivery Cart for Tight-Space Navigation
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Solution Overview
Problem
Existing autonomous robotic delivery carts have inflexible designs, leading to high manufacturing costs, limited customization, and inefficient operation, requiring manual payload loading and lacking adequate sensing systems for navigating tight spaces.
Innovation Solution
A customizable robotic delivery cart with a structural frame made from Aluminum extrusions, integrated navigational sensors, and propulsion systems, allowing easy modification and autonomous navigation, including LiDAR, TOF sensors, and a controller with an XML file for specific configurations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If rigid custom parts are manufactured for each robotic cart design, then the cart can be customized for specific use cases, but manufacturing costs increase significantly
Solution Approach 1:
The patent implements a universal robotic cart platform with standardized components (frame, enclosure, mounts, software stack) that can serve multiple use cases. The cart is designed to accommodate different payloads and operational requirements through configuration rather than physical redesign, allowing one platform to fulfill multiple functions across diverse applications.
Solution Approach 2:
The robotic cart system is divided into modular, independently replaceable components including the frame, enclosure, propulsion system, sensing system, and payload interface. This segmentation allows specific parts to be modified or swapped for different use cases without redesigning the entire system, reducing manufacturing costs while maintaining adaptability.
2Adaptability or versatility
If a whole new robotic cart is designed from scratch for different use cases, then the cart can accommodate specific operational requirements, but redesign time and cost increase
Solution Approach 1:
The robotic cart employs dynamic reconfigurability through software configuration and modular component assembly. Instead of static, fixed designs, the system can be dynamically adapted to different operational requirements by changing software parameters and swapping modular components, enabling rapid response to new use cases without time-consuming redesign cycles.
Solution Approach 2:
A single universal cart design serves multiple operational purposes through configurable software and modular attachments, eliminating the need to design new carts for each use case. The standardized platform can be quickly reconfigured for different payloads, environments, and operational modes.
3Reliability
If components and wiring are hardcoded in the software, then the cart operates reliably for its intended purpose, but customization becomes difficult and expensive
Solution Approach 1:
The software architecture is segmented into modular, independently configurable modules that map to physical hardware components. Each module can be configured and tested independently, maintaining reliability through standardized interfaces while enabling easy customization by modifying individual software modules without affecting the entire system.
Solution Approach 2:
The system uses parameter-based configuration where hardware interfaces and operational behaviors are defined through configurable parameters rather than hardcoded logic. This allows the same software framework to adapt to different hardware configurations and operational requirements by changing parameters, maintaining reliability through consistent software structure while enabling flexible customization.
4Device complexity
If few sensors are used to measure distance to obstacles, then the cart structure remains simple, but navigation capability in crowded spaces is insufficient
Solution Approach 1:
The sensing system merges multiple types of sensors (infrared, ultrasonic, LIDAR, cameras) into an integrated navigation system. These diverse sensors work together synergistically to provide comprehensive obstacle detection and navigation capabilities in crowded spaces, achieving superior performance without proportionally increasing structural complexity through unified sensor integration.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables cost-effective customization, efficient autonomous operation, and improved navigation in tight spaces, reducing manual intervention and enhancing operational efficiency.
Implementation Method 1
a Light Detection and Ranging (LiDAR) unit
Implementation Method 2
a stereo vision camera, a Light Detection and Ranging (LiDAR) unit, an array of ultrasonic sensors
Data Source
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AI summary
A system and a method for facilitating the autonomous navigation of a utility and delivery cart implements new means for a motorized cart to operate in different environments under specific operational conditions. The system includes a structural frame, a controller, a plurality of navigational sensors, a portable power source, a pair of caster wheels, and a pair of motorized wheels. The structural frame corresponds to the main structure of the system that can be customized to carry different payloads and accommodate different accessories. The pair of caster wheels and the pair of motorized wheels enable the movement of the structural frame. The controller and the plurality of navigational sensors allow the autonomous operation of the pair of motorized wheels under specific operational configurations. The portable power source provides the power necessary for the operation of the controller, the plurality of navigational sensors, and the pair of motorized wheels.