Robot Pixels Dynamic Texture Formation and Collision Avoidance
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Solution Overview
Problem
Existing display technologies with mobile pixels lack the ability to dynamically arrange themselves to represent arbitrary shapes or images in real-time, and existing methods for path planning for non-holonomic robots are either not real-time or inaccurate.
Innovation Solution
A system and method for generating a dynamic texture using mobile entities, which involves computing texture characterization parameters and goal positions based on input textures and actual entity positions, and using these goal positions to control the entities for collision-free movement to create visual representations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If mobile pixels are used to create dynamic visual representations, then adaptability and visual flexibility are improved, but real-time control accuracy and collision-free path planning are worsened
Solution Approach 1:
The system segments the visual representation task into discrete control steps: computing goal positions from texture characterization parameters, planning individual paths for each mobile entity, and executing motion. This segmentation allows real-time control while maintaining accuracy through systematic processing of each entity's trajectory independently.
Solution Approach 2:
The system performs preliminary computation of goal positions and path plans before executing mobile entity motion. By pre-computing texture characterization parameters and determining target positions in advance, the system ensures accurate positioning while maintaining real-time responsiveness during actual display operation.
2Manufacturing precision
If complex path planning algorithms are used for non-holonomic robots, then path planning accuracy is improved, but real-time computational speed is worsened
Solution Approach 1:
The path planning process is segmented into independent computations for each mobile entity, where goal positions are calculated separately based on texture parameters. This segmentation reduces computational complexity by avoiding global optimization problems, enabling real-time processing while maintaining individual path accuracy for each entity.
Solution Approach 2:
Each mobile entity determines its own path to the goal position using local computations based on texture characterization parameters. This self-service approach eliminates the need for complex centralized coordination, reducing computational overhead and enabling real-time path planning while maintaining accuracy through decentralized autonomous navigation.
3Adaptability or versatility
If mobile entities are deployed to form arbitrary shapes, then adaptability is improved, but collision avoidance capability is worsened
Solution Approach 1:
The system performs preliminary path planning that explicitly accounts for collision avoidance before mobile entities begin motion. By pre-computing trajectories that avoid collisions while achieving target shape configurations, the system ensures both adaptability in forming arbitrary shapes and reliability in collision-free operation during dynamic texture display.
Data Source
AI summary
Techniques are disclosed for controlling robot pixels to display a visual representation of a real-world video texture. Mobile robots with controllable color may generate visual representations of the real-world video texture to create an effect like fire, sunlight on water, leaves fluttering in sunlight, a wheat field swaying in the wind, crowd flow in a busy city, and clouds in the sky. The robot pixels function as a display device for a given allocation of robot pixels. Techniques are also disclosed for distributed collision avoidance among multiple non-holonomic and holonomic robots to guarantee smooth and collision-free motions.