Modular Robotic Posts for Adaptive Crowd Control
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Solution Overview
Problem
Existing robotic systems for crowd control and semantic augmentation lack versatility and efficiency in reconfiguring and adapting to dynamic environments, requiring significant manpower for setup and maintenance, and struggle with real-time information processing and semantic inference.
Innovation Solution
A modular robotic semantic system comprising smart posts with integrated modules such as power, antenna, optical sensor, and control sections, capable of autonomous movement and reconfiguration, using semantic routes and rules for semantic augmentation, signal conditioning, and video processing to adapt to changing conditions and provide real-time information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual reconfiguration is used for crowd control posts, then setup and maintenance require significant manpower, but the system lacks adaptability to dynamic environments
Solution Approach 1:
The robotic posts are equipped with autonomous navigation capabilities and self-reconfiguration mechanisms, allowing them to automatically adjust their positions and formations in response to environmental changes without human intervention. The system uses onboard sensors and processors to make real-time decisions about reconfiguration
Solution Approach 2:
The system transitions from static manual positioning to dynamic autonomous reconfiguration. The robotic posts can continuously adapt their configurations based on real-time environmental feedback, enabling fluid adjustments to crowd control formations without requiring manual repositioning
2Productivity
If traditional robotic systems are used for crowd control, then the devices can perform basic functions, but they lack semantic augmentation capabilities for real-time information processing
Solution Approach 1:
The robotic posts integrate multiple functional modules including optical sensors, wireless communication antennas, displays, speakers, and semantic processing units within a single platform. This multi-functional design enables the system to perform surveillance, communication, semantic inference, and crowd guidance simultaneously
Solution Approach 2:
The system architecture is divided into modular components: sensing modules for data collection, semantic processing modules for inference, communication modules for information exchange, and actuation modules for physical response. This segmentation allows independent optimization of each function while maintaining system integration
3Adaptability or versatility
If fixed configuration posts are used, then the structure is simple and stable, but the system cannot reconfigure to respond to changing conditions
Solution Approach 1:
The posts incorporate movable components including wheels or casters for mobility, telescopic sections for height adjustment, and articulating arms for accessory positioning. These dynamic elements allow the posts to change their physical configurations in response to environmental conditions while maintaining structural integrity
Solution Approach 2:
The post structure is divided into modular sections that can be independently positioned or reconfigured. Each module can be attached or detached as needed, allowing flexible reconfiguration of the overall system architecture without requiring complete system redesign
Data Source
AI summary
A generative sensing system includes a plurality of fairings attached to a carrier via a plurality of mechanical links and further associated with a plurality of actuators in communication with a computing system and a memory in communication with the computing system storing a plurality of fairing groups. The computer system is configured to receive and input from a sensor and adjust the fairing groups to capture an agent flow which is transduced to a voltage and transferred to an electrical energy storage and/or distribution system.