Remote Control Point-Cloud Estimation for Accuracy-Speed Tradeoffs
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Solution Overview
Problem
There is a trade-off between estimation accuracy and processing time in remote control systems for movable bodies, making it challenging to balance accuracy and speed in real-time position and orientation estimation using three-dimensional point cloud data from distance measurement devices.
Innovation Solution
A remote control device dynamically specifies and adjusts the number of processing-object distance measurement devices based on required accuracy and traveling situations, prioritizing either estimation accuracy or processing speed by increasing or decreasing the number of devices as needed, and adjusting movement velocity to maintain stability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the number of distance measurement devices used in estimation processing is increased, then estimation accuracy is improved, but processing time increases
Solution Approach 1:
The patent applies dynamics by making the number of processing-object distance measurement devices adjustable rather than fixed. The control device dynamically changes the number of devices based on the required accuracy level and traveling situation, allowing the system to adapt between high accuracy (more devices) and fast processing (fewer devices) modes as needed
Solution Approach 2:
The patent changes the parameter of the number of processing-object distance measurement devices according to different operating conditions. When high accuracy is required, more devices are selected; when processing speed is prioritized, fewer devices are used. This parameter adjustment resolves the contradiction between accuracy and processing time
2Measurement precision
If the number of processing-object distance measurement devices is increased to maintain high estimation accuracy, then device complexity increases
Solution Approach 1:
The system dynamically adjusts the number of active processing objects based on required accuracy levels. Instead of always using all available distance measurement devices, the system selectively activates only the necessary number, reducing complexity when high accuracy is not required while maintaining the capability for high accuracy when needed
Solution Approach 2:
The patent changes the operational parameter of device count based on accuracy requirements. By adjusting this parameter, the system avoids the constant high complexity that would result from always using all devices, while still achieving high accuracy when the situation demands it
3Productivity
If processing speed is prioritized by using fewer distance measurement devices, then estimation accuracy decreases
Solution Approach 1:
The system dynamically switches between processing modes based on the required accuracy level. When fast processing is needed, fewer devices are used for higher speed; when accuracy is prioritized, more devices are activated. This dynamic switching allows the system to optimize for either speed or accuracy depending on real-time requirements
Solution Approach 2:
The patent adjusts the parameter of device count to match the prioritized objective. For speed-critical operations, a lower device count parameter is selected; for accuracy-critical operations, a higher device count parameter is used, allowing flexible optimization of the speed-accuracy trade-off
Data Source
AI summary
A remote control device that generates a control command for remote control of a movable body, using measurement results of a plurality of distance measurement devices, and that sends the control command to the movable body, includes one or more memories, and one or more processors in communication with the one or more memories, configured to perform processes including, specifying one or more processing-object distance measurement devices from the plurality of distance measurement devices, each of the processing-object distance measurement devices being a distance measurement device that is used in estimating at least one of the position and orientation of the movable body; and executing the estimating using three-dimensional point cloud data that is obtained through measurement by the processing-object distance measurement devices.