Methods for finding the perimeter of a place using observed coordinates
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Solution Overview
Problem
Current robotic mapping techniques require significant computational power and often rely on inaccurate sensor statistics, leading to poor performance, and may necessitate additional components like beacons, which increase costs and space requirements.
Innovation Solution
A method using a robotic device equipped with sensors to obtain spatial data, translate depth data into a workspace frame of reference, and navigate to create a spatial map, segmenting the workspace into zones based on layout, while using image processing to estimate depths and update the map without the need for extensive feature point extraction or additional components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If EKF technique is used to map the environment with feature points, then mapping accuracy is improved, but computational power requirement increases significantly
Solution Approach 1:
The patent extracts only the essential perimeter boundary information from the environment rather than processing all feature points. By focusing solely on perimeter detection and using a simplified coordinate system approach, the system eliminates the need for computationally intensive EKF processing while maintaining adequate mapping accuracy for perimeter identification.
Solution Approach 2:
The patent employs a lightweight, computationally inexpensive mapping approach that sacrifices the high precision of EKF in exchange for significantly reduced processing requirements. The simplified method uses basic coordinate transformations and perimeter tracking algorithms that require minimal computational resources compared to full EKF implementation.
2Area of stationary object
If distance sensor rotates 360-degrees to map the environment, then complete environment coverage is achieved, but the robotic device must rotate before performing work
Solution Approach 1:
The patent performs preliminary perimeter detection by having the robotic device navigate along the environment boundaries first, identifying perimeter coordinates before attempting to map internal areas. This preliminary action of tracing the perimeter first allows subsequent mapping operations to be more efficient and targeted.
Solution Approach 2:
The patent uses dynamic navigation where the robotic device moves continuously through the environment, detecting perimeters on-the-fly during its traversal rather than performing a static 360-degree rotation at fixed positions. This dynamic approach allows mapping to occur concurrently with movement, reducing total mapping time.
3Loss of information
If occupancy map tracks all points including perimeters and empty spaces, then comprehensive environment representation is achieved, but computational cost increases
Solution Approach 1:
The patent extracts only the perimeter boundary coordinates from the environment rather than tracking all occupancy points. By focusing exclusively on perimeter detection and storing only boundary coordinate information in a simplified data structure, the system achieves adequate environment representation for perimeter-based operations while dramatically reducing computational storage and processing requirements.
4Measurement precision
If beacons are placed within the environment for mapping, then mapping accuracy is improved, but additional components increase costs and space requirements
Solution Approach 1:
The patent enables the robotic device to perform self-localization and perimeter detection using its own motion sensors and depth sensors without requiring external beacon infrastructure. The system uses its tracked position and observed depth measurements to autonomously identify perimeter boundaries, eliminating the need for beacons or other external reference components.
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
This approach provides a computationally inexpensive and cost-effective method for marking the perimeter of a workspace, reducing processing requirements and eliminating the need for additional components, allowing the robotic device to efficiently map and operate within the environment.
Implementation Method 1
a first sensor, the depth sensor, is used to obtain the depth data
Implementation Method 2
a second sensor, the image sensor, is used to obtain a stream of images of spatial surroundings of the robot
Data Source
AI summary
Provided is a medium storing instructions that when executed by one or more processors effectuate operations including: obtaining a stream of spatial data indicative of a robot's position in a workspace; obtaining a stream of movement data indicative of the robot's displacement in the workspace; navigating along a path of the robot in the workspace based on the stream of spatial data; while navigating, mapping at least part of the workspace based on the stream of spatial data to form or update a spatial map in memory; wherein the spatial map expands as new areas of the workspace are covered by the robot and spatial data of the new areas of the workspace are obtained and used by the one or more processors to update the spatial map; and wherein the spatial map of the workspace is segmented into two or more zones.