Autonomous Cart Robot Docking for Vehicle Trunk Loading
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Solution Overview
Problem
Manual loading and unloading of objects from vehicle trunks is cumbersome, especially for elderly individuals, and requires significant time and effort, necessitating a solution for automated assistance.
Innovation Solution
An autonomous cart robot that can dock itself within a vehicle's trunk without human assistance, equipped with sensors and motorized wheels, allowing it to act as a shopping cart outside the vehicle and automatically load/unload objects into the trunk.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual loading and unloading is performed, then the process can be completed with simple equipment, but it requires significant physical effort and time
Solution Approach 1:
The robot performs loading and unloading operations autonomously without human assistance. It navigates independently, identifies objects, and executes transfer operations automatically, allowing the system to serve itself rather than requiring manual operation.
Solution Approach 2:
The patent replaces manual mechanical operations with an automated robotic system equipped with sensors, processors, and actuators. The robot uses computer vision and navigation systems to substitute human physical effort with automated mechanical and electronic systems.
2Ease of operation
If automated loading/unloading is implemented, then physical strain on users is reduced, but the device complexity increases
Solution Approach 1:
The robot is designed to perform multiple functions including navigation, object identification, loading, unloading, and trunk integration. This multi-functionality consolidates various separate systems into a single universal device, reducing the need for multiple specialized machines.
Solution Approach 2:
The robot acts as an intermediary between the user and the vehicle trunk. It handles the intermediate task of transferring objects, mediating between the user's intent and the physical loading/unloading process, thereby reducing direct user burden.
3Extent of automation
If the robot docks automatically in the trunk, then human assistance is eliminated, but the docking mechanism becomes more complex
Solution Approach 1:
The robot uses sensors and vision systems to continuously monitor its position and environment during docking. This feedback allows the robot to adjust its movements in real-time, achieving automatic docking through closed-loop control rather than complex mechanical guidance systems.
Solution Approach 2:
The automatic docking mechanism replaces complex mechanical alignment systems with sensor-based navigation and computer vision. The robot uses electronic sensing and processing to achieve precise docking without requiring complex mechanical docking structures.
4Reliability
If the robot follows users and recognizes obstacles, then navigation safety is improved, but sensor and processing requirements increase
Solution Approach 1:
The robot performs preliminary obstacle detection and path planning before executing movement. By identifying potential hazards and planning safe routes in advance, the system ensures navigation safety without requiring overly complex real-time response systems.
Solution Approach 2:
The robot continuously monitors its environment using sensors and adjusts its navigation based on real-time feedback. This ongoing sensing and adjustment ensures safe navigation while using relatively simple sensor systems that react to current conditions rather than requiring complex predictive models.
Data Source
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AI summary
A system may include a vehicle having a storage area and a guide rail configured to extend from the storage area. The system may further include a robot having a support portion comprising a placement surface and a base. The robot may also include a plurality of descendible wheels. The robot may also further include a plurality of legs, each connecting the support portion to one of the plurality of descendible wheels.