Telepresence Robot Localization Using Live Markers for Adaptive Navigation
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Solution Overview
Problem
Current teleconferencing robotic systems are not intelligent enough to navigate based on specific paths, fail to focus on presenters, and lack location-based intelligence, making them inflexible and unable to adapt to changing environments.
Innovation Solution
A processor-implemented method and system for dynamic localization of a telepresence robot using live markers, which involves image processing to identify markers, decode identifiers, and navigate based on parameters such as size, location, and orientation, allowing the robot to adapt its path and content delivery in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If fixed video conference facilities are used, then setup cost is reduced, but location-based intelligence and flexibility are lost
Solution Approach 1:
The patent introduces live markers as intermediary objects placed at specific locations in the environment. These markers serve as mediators between the telepresence robot and the fixed infrastructure, providing location-based intelligence without requiring complex fixed video conference facilities. The markers contain encoded spatial information that the robot can decode to understand its environment and navigate autonomously.
Solution Approach 2:
The telepresence robot equips itself with an image capturing device and processing capabilities to autonomously detect, decode, and utilize information from live markers. The system performs self-navigation and self-localization by processing marker data in real-time, eliminating the need for complex external control infrastructure while gaining location-based intelligence.
2Adaptability or versatility
If telepresence robot navigation is made flexible and adaptive, then location-based awareness is improved, but path navigation precision is reduced
Solution Approach 1:
The system implements continuous feedback loops where the robot captures images of live markers, decodes their spatial information, compares current position with target location, and adjusts its navigation path accordingly. The live markers provide real-time feedback on location and orientation, enabling the robot to dynamically adapt its path while maintaining precise navigation through iterative correction.
Solution Approach 2:
The patent employs dynamic path planning where the robot's navigation route is not fixed but continuously adjusted based on real-time marker detection and environmental conditions. The system transitions from static pre-programmed paths to dynamic adaptive navigation, allowing the robot to recalculate optimal routes while maintaining precision through continuous marker-based localization.
3Speed
If image processing is performed in real-time to identify live markers, then navigation speed is improved, but processing complexity increases
Solution Approach 1:
The live markers are pre-configured with encoded spatial information including location, orientation, and navigation instructions. This preliminary encoding of data in the markers allows the robot to perform simpler decoding operations in real-time rather than complex image analysis, achieving fast navigation while reducing onboard processing complexity. The heavy computational burden is shifted to the marker preparation phase.
Solution Approach 2:
The patent extracts only the essential navigation information needed for real-time decision-making from the full image data. Instead of processing entire images for navigation, the system extracts key features such as marker position, orientation, and encoded path information, significantly reducing processing complexity while maintaining navigation speed. Non-essential visual data is discarded rather than processed.
Data Source
AI summary
Currently teleconferencing robotic systems available are not smart and unable to navigate based on specific path and fail to focus on presenter based on overall environment. This disclosure relates to method of dynamic localization of a telepresence robot based on plurality of live markers. A plurality of images is received from an image capturing device connected to the telepresence robot. The plurality of images is processed to identify the plurality of live markers in a path of the telepresence robot. A binary matrix is decoded to identify at least one identifier (ID) associated with the at least one live marker from the plurality of live markers. A plurality of parameters is identified based on the at least one ID associated with the at least one live marker. A further path is dynamically localized to navigate the telepresence robot based on the plurality of parameters and the plurality of live markers.