Dynamic Target Detection and Tracking with Coordinated Robot Fleets
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Solution Overview
Problem
In dynamic warehouse environments, robots face challenges in locating a target whose exact location is unknown, particularly when the target is moving and out of the robot's field of vision, leading to inefficiencies in 'follow-me' or 'guide-me' operations.
Innovation Solution
A Fleet Management System (FMS) coordinates a fleet of robots to assist in finding and tracking the target by utilizing identifiers such as facial recognition, gait analysis, or clothing attributes, employing passive, semi-active, and active search modes to locate the target, allowing other robots to continue their tasks while searching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single robot performs follow-me or guide-me operations using facial recognition or predefined search patterns, then the robot can track a target operator, but the robot becomes inefficient when the target's current location is unknown or the target moves out of the robot's field of vision
Solution Approach 1:
The system divides the target detection task among multiple robots in a fleet. Each robot independently searches for the target using its own sensors and processing capabilities, rather than relying on a single robot to perform all detection functions. This segmentation allows parallel search operations across multiple areas simultaneously.
Solution Approach 2:
The system combines the detection capabilities of multiple robots into a coordinated fleet operation. The Fleet Management System integrates information from multiple robots to locate and track the target, merging individual robot efforts into a collective search strategy that improves both reliability and efficiency.
2Reliability
If the robot continuously searches for the target using active search patterns, then the target can be located more reliably, but other robots cannot continue their previously assigned tasks
Solution Approach 1:
Robots perform partial search actions rather than complete active search patterns. When a robot detects the target, it performs sufficient detection actions to locate and track the target, while other robots maintain their normal task performance. This partial action approach ensures target detection without requiring all robots to engage in exhaustive search behaviors.
Solution Approach 2:
The Fleet Management System automatically coordinates the search and tracking operations without requiring manual intervention. The system self-manages the allocation of search tasks, processes detection data from multiple robots, and maintains target tracking autonomously, allowing robots to continue their assigned tasks while the system handles the coordination of target location efforts.
Data Source
AI summary
A device includes a memory, configured to store an identifier corresponding to a target; and a processor, configured to send the identifier to one or more first robots; instruct the one or more first robots to search for the target using the identifier, receive a position of the target from a first robot of the one or more first robots; and instruct a second robot to travel to the position.