Door-Aware Delivery Robot Control for Safe Goods Unloading
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Solution Overview
Problem
Current mobile robots face challenges in efficiently delivering goods when the recipient's location differs from the delivery destination, as they require user intervention for goods receipt, which is inconvenient and inefficient.
Innovation Solution
A robot equipped with AI technology and machine learning algorithms, utilizing an AI device and server for autonomous operation, including image analysis and sensor data processing to determine the target position and unload goods safely without disturbing the recipient's path, by identifying door features and determining the optimal unloading position.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the mobile robot delivers goods to a delivery destination, then the delivery task is completed, but the recipient cannot receive goods directly when their current location differs from the delivery destination
Solution Approach 1:
The robot performs preliminary actions by delivering goods to the recipient's current location instead of the original delivery destination. The system identifies the recipient's position through image recognition and sensor data, then adjusts the delivery location in advance to match where the recipient actually is, eliminating the need for the recipient to move to the delivery destination.
Solution Approach 2:
The robot autonomously determines whether the recipient is present at the delivery destination by analyzing image data and sensor information. When the recipient is not found at the destination, the robot independently decides to deliver to an alternative location (the recipient's current position) without requiring user intervention or manual reconfiguration.
2Productivity
If the robot autonomously determines target position using AI technology, then delivery efficiency is improved, but the device complexity increases
Solution Approach 1:
The AI device and server perform multiple functions: they capture images, recognize the recipient, determine the recipient's current position, analyze sensor data, and calculate the optimal delivery location. This multi-functional approach consolidates what would otherwise require separate systems into a unified AI platform, managing complexity while enhancing autonomous capability.
Solution Approach 2:
The server acts as an intermediary between the mobile robot and the delivery destination. It receives image data and sensor information from the robot, processes this information to determine the recipient's location, and returns the calculated target position to the robot. This intermediary architecture distributes computational complexity across multiple components rather than concentrating it all in the robot.
3Reliability
If the robot delivers goods to the delivery destination, then the delivery task is completed, but the recipient may be disturbed if they are not at the delivery destination
Solution Approach 1:
The system uses feedback from image recognition and sensor data to continuously monitor whether the recipient is present at the delivery destination. Based on this feedback, the robot adjusts its delivery location in real-time. If the recipient is not at the destination, the system receives feedback about the recipient's actual position and modifies the target position accordingly, ensuring accurate delivery without disturbance.
Data Source
AI summary
A robot and a method for controlling the robot are provided. The robot includes: at least one motor provided in the robot; a camera configured to capture an image of a door; and a processor configured to determine, on the basis of at least one of depth information and a feature point identified from the image, a target position not overlapping with a moving area of the door, and control the at least one motor such that predetermined operations are performed with respect to the target position. The feature point includes at least one of a handle and a hinge of the door.