Walking Assist Robot Using Pre-Mapped Environment Data
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Solution Overview
Problem
Existing walking assist robots lack the ability to automatically adapt their assistive modes based on the wearer's environment, leading to reduced usability and increased power consumption due to the need for active sensors like laser sensors or depth cameras.
Innovation Solution
A walking assist robot equipped with a location detector, walking environment determiner, and control mode selector that uses pre-mapped environment information to automatically select an appropriate assistive mode, eliminating the need for active sensors and enhancing usability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If active sensors (laser sensor or depth camera) are used to recognize walking environment, then environment recognition capability is improved, but device complexity and power consumption increase
Solution Approach 1:
The patent uses a pre-built map that copies environmental information (walkable areas, obstacles, terrain) obtained by a mapping robot, instead of requiring active sensors on the walking assist robot to perceive the environment in real-time. This allows the robot to navigate using stored environmental data rather than active sensing.
Solution Approach 2:
The environment mapping is performed in advance by a mapping robot before the walking assist robot needs to navigate. The map is pre-built and stored, so when the walking assist robot operates, it can immediately use the pre-prepared environmental information without needing to perform real-time sensing.
2Measurement precision
If active sensors (laser sensor or depth camera) are used to recognize walking environment, then environment recognition capability is improved, but power consumption increases
Solution Approach 1:
The patent uses a pre-built map that copies environmental information (walkable areas, obstacles, terrain) obtained by a mapping robot, instead of requiring active sensors on the walking assist robot to perceive the environment in real-time. This allows the robot to navigate using stored environmental data rather than active sensing.
Solution Approach 2:
The environment mapping is performed in advance by a mapping robot before the walking assist robot needs to navigate. The map is pre-built and stored, so when the walking assist robot operates, it can immediately use the pre-prepared environmental information without needing to perform real-time sensing.
3Measurement precision
If active sensors are used for environment recognition, then real-time environment detection is improved, but usability decreases due to complex operation requirements
Solution Approach 1:
The system automatically uses the pre-built map to determine the wearer's location and select appropriate walking assistance modes without requiring user input or manual configuration. The robot self-determines its operational parameters based on stored environmental data, eliminating the need for users to manually provide environment information.
Solution Approach 2:
The environment mapping is performed in advance by a mapping robot before the walking assist robot needs to navigate. The map is pre-built and stored, so when the walking assist robot operates, it can immediately use the pre-prepared environmental information without needing to perform real-time sensing.
4Use of energy by moving object
If pre-mapped environment information is used, then power consumption is reduced, but recognition accuracy may deteriorate due to line of sight restrictions
Solution Approach 1:
The patent uses a pre-built map that copies environmental information (walkable areas, obstacles, terrain) obtained by a mapping robot, instead of requiring active sensors on the walking assist robot to perceive the environment in real-time. This allows the robot to navigate using stored environmental data rather than active sensing.
Solution Approach 2:
The pre-built map serves as an intermediary that contains comprehensive environmental information. Instead of directly sensing the environment (which may be blocked by line of sight), the system queries the map as an intermediate data source that already contains the necessary environmental knowledge, including areas that may not be directly visible.
Data Source
AI summary
A control method of a walking assist robot, may include: estimating a wearer's location on a map including walking environment information; determining a walking environment in a direction in which the wearer moves; and selecting a control mode for assisting the wearer's walking according to the walking environment.