Mobile Robot Recognition Control for Situational Power Saving
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Solution Overview
Problem
Existing control systems for mobile robots in environments with both familiar and unfamiliar people, such as hospitals, face constant processing loads, leading to high power consumption without an effective way to adjust based on situational changes.
Innovation Solution
A control system that dynamically switches between operation modes based on the presence of familiar (staff) or unfamiliar (non-staff) individuals, using different processing loads and device settings to reduce power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If human recognition is performed without distinguishing between familiar and unfamiliar people, then all people can be recognized uniformly, but processing load is constantly high leading to high power consumption
Solution Approach 1:
The system dynamically adjusts the recognition processing load based on the presence of unfamiliar people. When unfamiliar people are detected, the system switches to a first operation mode with higher processing load for accurate recognition. When only familiar people are present, it switches to a second operation mode with reduced processing load, thereby optimizing power consumption while maintaining necessary recognition accuracy.
Solution Approach 2:
The system changes the processing parameters of the human recognition function based on situational context. By identifying whether unfamiliar people are present, the system adjusts the processing load parameter, switching between different operation modes that have different computational requirements, thus reducing power consumption when high-level recognition is not needed.
2Measurement precision
If high processing load is applied for accurate human recognition, then recognition accuracy is improved, but power consumption increases
Solution Approach 1:
The system applies partial action by adjusting the processing load to match the actual need. When unfamiliar people are present, full processing load is applied for accurate recognition. When only familiar people are present, reduced processing load is sufficient, avoiding excessive computation and power consumption while still maintaining adequate recognition functionality.
3Adaptability or versatility
If the system always maintains high processing capability for human recognition, then recognition accuracy is maintained, but the system cannot adapt to different situations leading to wasted energy
Solution Approach 1:
The system dynamically adapts its processing capability based on situational context by detecting the presence of unfamiliar people. This dynamic adjustment allows the system to be versatile - maintaining high accuracy when needed while reducing power consumption when full capability is not required, thus achieving both adaptability and energy efficiency.
Data Source
AI summary
A control system according to the present disclosure executes system control that controls a system including a mobile robot that autonomously moves. The control system executes a group classification process of recognizing a feature of a person present around the mobile robot and classifying, based on the feature, the person into a preset first group or second group. The control system above selects a first operation mode when the person belonging to the first group is present around the mobile robot and selects a second operation mode that is different from the first operation mode when the person belonging to the first group is not present around the mobile robot. The control system above controls, when the second operation mode is selected, the group classification process so as to execute a process with a smaller processing load than a processing load when the first operation mode is selected.