Robot Confinement Using Surface Indentation Virtual Boundaries
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Solution Overview
Problem
Existing methods for confining robotic devices are inefficient and impractical, requiring large physical barriers, extensive memory for navigation systems, or aesthetically unpleasing and hazardous cables, which complicate setup and reconfiguration for different environments.
Innovation Solution
A robotic system using a line laser diode and image sensor to detect predefined surface indentation patterns, creating virtual boundaries that allow the robot to autonomously recognize and navigate within or avoid specific areas, reducing the need for physical barriers and memory-intensive programming.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If large physical barriers are used to confine robotic devices, then the robot is blocked from entering restricted areas, but the barriers encumber routine movement and require substantial setup
Solution Approach 1:
The patent replaces physical mechanical barriers with an optical detection system. The robotic device uses an image sensor to detect boundary components (visual markers) that define restricted areas. This substitution eliminates the need for large physical barriers while maintaining confinement effectiveness, allowing free movement in permitted areas while reliably preventing entry into restricted zones through visual recognition and navigation away from boundary markers.
2Adaptability or versatility
If sophisticated navigation systems with stored maps are used, then the robot can travel along predetermined paths, but large amounts of memory are required and re-programming is needed for each new location
Solution Approach 1:
The robotic device performs self-mapping and self-localization by detecting boundary components and environmental features in real-time using its image sensor. Instead of relying on pre-stored maps requiring large memory, the robot builds and updates its environmental representation dynamically during operation. This allows adaptation to new locations without re-programming or extensive memory resources, as the system serves itself by autonomously creating navigation data from sensor input.
3Measurement precision
If cables or wires are installed to define boundaries, then the area limits are clearly marked, but the installation is difficult and creates aesthetic issues and tripping hazards
Solution Approach 1:
The patent replaces physical cable or wire boundary markers with visual boundary components that can be detected by the robot's image sensor. These boundary components may be painted markers, stickers, or other visual indicators that are easily applied to surfaces. This substitution maintains precise boundary definition accuracy while dramatically reducing installation complexity, eliminating tripping hazards, and improving aesthetics compared to traditional cable-based systems.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables efficient and flexible confinement of robotic devices within environments by using existing surface features to define virtual boundaries, reducing human intervention and setup complexity while allowing for adaptive operation across various locations.
Implementation Method 1
A robotic system using a line laser diode and image sensor to detect predefined surface indentation patterns
Implementation Method 2
The line laser diode and image sensor to detect predefined surface indentation patterns
Implementation Method 3
capturing, with an image sensor disposed on the robot, images of objects within an environment of the robot
Data Source
AI summary
A method for determining at least one action of a robot, including capturing, with an image sensor disposed on the robot, images of objects within an environment of the robot as the robot moves within the environment; identifying, with a processor of the robot, at least one object based on the captured images; marking, with the processor, a location of the at least one object in a map of the environment; and actuating, with the processor, the robot to execute at least one action based on the at least one object identified.