Autonomous Mobile Device Target Search Route Prioritization
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Solution Overview
Problem
Existing autonomous mobile devices, such as robots and drones, face challenges in efficiently rediscovering a tracking target when it deviates from their field of view, especially at intersections or branch routes, leading to decreased processing efficiency and inability to track targets that try to escape.
Innovation Solution
An information processing device with a tracking target position estimation unit and a tracking target search unit that calculates and prioritizes search routes based on proximity to the estimated target position, allowing the mobile device to efficiently search for and reacquire the target by moving along selected routes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the mobile device waits for the tracking target to enter its field of view before turning at an intersection, then the tracking target can be reliably detected, but the processing efficiency decreases due to waiting time
Solution Approach 1:
The system performs preliminary actions by calculating multiple candidate movement routes and estimating the tracking target's position before actually moving. By preparing search routes in advance and selecting the most promising one based on estimated target position, the mobile device can turn at intersections without waiting for the target to enter its field of view, thus improving efficiency while maintaining reliability
Solution Approach 2:
The system uses feedback from the tracking target position estimation unit to continuously update which search route to follow. By monitoring the estimated target position and comparing it with candidate routes, the system dynamically selects the route most likely to contain the target, enabling efficient navigation through intersections without unnecessary waiting
2Device complexity
If the mobile device moves to a position assuming the tracking target exists at a past observation position without estimation processing, then the device complexity is reduced, but the ability to track targets that escape or take unexpected routes deteriorates
Solution Approach 1:
The system performs preliminary position estimation of the tracking target before movement, calculating where the target is likely to be based on past observations and current movement state. This preliminary estimation enables the device to proactively navigate to positions where the target is expected to appear, improving adaptability to escaping or diverging targets while maintaining relatively simple processing
Solution Approach 2:
The tracking target position estimation unit acts as an intermediary between past observations and future actions. It processes past tracking data to generate estimated current position information, which then guides route selection and movement decisions, bridging the gap between simple reactive movement and complex adaptive tracking
Data Source
AI summary
A tracking target position estimation unit and a tracking target search unit that searches for a tracking target are included. The tracking target search unit calculates one or more search routes connecting a current position of the mobile device and a position where the tracking target can exist, generates a search route list in which the calculated one or more search routes are arranged from the top in order of proximity to a tracking target estimated position, and selects a search route in order from the top of the generated search route list, and moves the mobile device according to the selected search route to search for the tracking target. It is determined whether or not the tracking target has been detected based on an image captured by a camera mounted on the mobile device, and in a case where the tracking target has been detected, tracking processing is resumed.