Method for setting parameters in an autonomous working device and an autonomous working device
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Solution Overview
Problem
Autonomous working devices face challenges in adapting to varying operating environments, leading to inefficient performance and potential unpredictable behavior due to unsuitable parameter combinations, which existing methods like online parameter adjustment with look-up tables and image analysis cannot fully address.
Innovation Solution
Generating and optimizing multiple parameter sets for different working environments during development, selecting the most suitable set based on sensor data from similar environments, and automatically setting these parameters to ensure optimal control and performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If parameters are adjusted to individual working environment after device delivery, then working efficiency is improved, but parameter interaction causes unpredictable behavior and degraded performance
Solution Approach 1:
The patent applies preliminary action by pre-generating multiple parameter sets during the development phase, each optimized for specific working environments. The system stores these pre-configured parameter sets in the device, so when deployed, it can directly select the appropriate pre-prepared parameter set based on the detected environment, avoiding the need for customers to manually adjust parameters and preventing unpredictable interactions.
2Adaptability or versatility
If multiple parameters are made adjustable for environment adaptation, then working efficiency is improved, but the complexity of parameter combination increases making it almost impossible to avoid unwanted behavior
Solution Approach 1:
The patent segments the parameter space by creating multiple distinct parameter sets, each tailored to specific working environments. Instead of allowing continuous adjustment of many parameters, the system divides parameters into discrete, pre-optimized groups that can be selected as complete packages, significantly reducing the complexity of parameter combinations while maintaining adaptability.
Solution Approach 2:
The patent applies parameter changes by pre-defining multiple parameter sets with different parameter values optimized for different working environments. The system changes parameters by selecting between these pre-defined sets rather than allowing arbitrary adjustment, which simplifies the adaptation process while maintaining environment-specific optimization.
3Reliability
If default parameter values are set by manufacturer, then safe operation is ensured, but working efficiency is compromised as a compromise for all environments
Solution Approach 1:
The patent applies universality by creating a multi-functional parameter system where a single device can operate efficiently in multiple different working environments. By incorporating multiple parameter sets that cover various environments, the device achieves both safe operation (through pre-tested parameter sets) and high working efficiency (by selecting the environment-optimized set), eliminating the need for a compromise default configuration.
4Adaptability or versatility
If online parameter adjustment is performed using look-up tables and image analysis, then specific parameters can be changed, but the resulting parameter combination may be completely useless or even allow risky operation
Solution Approach 1:
The patent applies preliminary action by pre-generating and validating multiple parameter sets during the development phase. Each parameter set is pre-configured for specific working environments and pre-tested for safety and effectiveness. During online operation, the system only selects from these pre-validated sets based on environment detection, avoiding the risks of generating unsafe parameter combinations through real-time calculation.
Data Source
AI summary
A system and method are provided for setting parameters in an autonomous working device. The autonomous working device can be controlled based on a plurality of parameters. For each of a plurality of different working environments a set of sensor values is generated. The plurality of sets is partitioned into categories, each category corresponding to a prototypical working environment. The parameters for each category are optimized to find an optimized parameter set for each prototypical working environment. For an individual working environment, an individual set of sensor values that the sensors of the autonomous working device produce is generated. Based at least on the individual set of sensor values, the prototypical working environment showing highest similarity to the individual environment is determined, and the parameters in the autonomous working device are set according to the optimized parameter set corresponding to the determined prototypical working environment.