Moving Robot Low Noise Mode Activation Using AI Ambient Sensing
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Solution Overview
Problem
Conventional moving robots generate noise during operations, which can be disruptive in situations like conversations or quiet activities, and existing noise reduction methods either increase manufacturing costs or reduce operational efficiency.
Innovation Solution
A moving robot equipped with a sensing unit to detect ambient situations and a controller that automatically activates or deactivates a low noise mode based on sensed conditions, such as user behavior and distance, to adjust noise levels accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If noise reduction devices are added to the moving robot, then noise levels are reduced, but manufacturing costs increase
Solution Approach 1:
The patent implements a dynamic noise control system that adjusts the operating mode of the moving robot based on real-time environmental detection. The controller switches between high-noise/high-efficiency mode and low-noise/low-efficiency mode depending on whether users are present and what activities they are performing, eliminating the need for permanent noise reduction hardware while achieving context-appropriate noise levels.
Solution Approach 2:
The system changes operational parameters (speed, power consumption, noise output) based on detected environmental conditions. When users are performing quiet activities like reading or watching TV, the robot reduces its operational parameters to minimize noise, whereas during conversations or active periods, it operates at full performance, thus avoiding both constant noise and permanent hardware additions.
2Productivity
If the moving robot operates at high power to maintain efficiency, then productivity is improved, but noise generation increases
Solution Approach 1:
The robot dynamically adjusts its operational state based on real-time environmental feedback from sensors. When the detection unit identifies users engaged in quiet activities within a certain distance, the controller transitions to a low-power, low-noise operational mode. When no such conditions are detected, the robot operates at high power for maximum productivity, thus achieving variable performance matching environmental needs.
Solution Approach 2:
The system employs a feedback loop where the detection unit continuously monitors environmental conditions (user presence, activity type, distance) and feeds this information to the controller, which then adjusts operational parameters accordingly. This closed-loop control enables the robot to respond adaptively to environmental context, balancing productivity and noise generation based on actual conditions rather than operating at fixed performance levels.
Data Source
AI summary
The moving robot using artificial intelligence includes: a traveling unit to move a main body; an operation unit to perform a specific operation while generating noise; a sensing unit to sense an ambient situation during traveling; and a controller to determine whether a specific activation condition is satisfied, based on situation information sensed by the sensing unit, and, when the activation condition is determined to be satisfied during traveling, perform a control action to activate a low noise mode so that the operation unit performs the specific operation with relatively reducing the noise. The control method using artificial intelligence includes: determining whether a specific activation condition is satisfied, based on situation information acquired by sensing an ambient situation during traveling; and, when the activation condition is determined to be satisfied, performing a specific operation in an activated state of a low noise mode in which noise is relatively reduced.