Mobile Robot Route Selection for Security Patrol and RFID Mapping
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Solution Overview
Problem
The adoption of robots in commercial and industrial settings has outpaced the implementation of robots in environments requiring frequent human interactions, particularly in retail and security contexts, where robots are needed for security operations, infrastructure management, navigation, and inventory management.
Innovation Solution
A mobile robot equipped with sensors, communication interfaces, and a fabric housing that enables interaction with building infrastructure, security systems, and human operators, capable of performing security operations, navigation, and inventory management, and generating semantic maps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a mobile robot is deployed for security operations and navigation in commercial settings, then security monitoring and patrol capabilities are improved, but the complexity of integrating with building infrastructure and security systems increases
Solution Approach 1:
The robot system is divided into modular components including sensor modules (cameras, LIDAR, microphones), navigation modules, communication modules, and processing units. Each module can be independently developed, tested, and replaced, reducing the complexity of integrating with building infrastructure while maintaining reliable security monitoring capabilities.
Solution Approach 2:
The mobile robot is designed with multi-functional capabilities including security patrol, inventory management, infrastructure monitoring, and human interaction. By consolidating these functions into a single platform with standardized interfaces, the system reduces overall integration complexity while enhancing comprehensive security monitoring and operational reliability.
2Reliability
If the robot is equipped with multiple sensors and communication interfaces for comprehensive security operations, then the ability to detect and respond to security risks is improved, but the device complexity and cost increase
Solution Approach 1:
Multiple sensor types (cameras, LIDAR, microphones, RFID readers) and communication interfaces are integrated into a unified sensor fusion platform. This consolidation allows the robot to process data from all sensors through a single processing pipeline, improving security risk detection while managing complexity through integrated architecture rather than separate systems.
Solution Approach 2:
A central processing unit or sensor fusion module acts as an intermediary between various sensors and the robot's decision-making systems. This intermediary layer standardizes data formats, filters redundant information, and coordinates sensor operations, thereby improving detection reliability while reducing the complexity burden of managing multiple sensors and interfaces.
3Productivity
If the robot autonomously selects routes based on security priorities and real-time conditions, then the productivity and responsiveness of security operations are improved, but the complexity of navigation and decision-making algorithms increases
Solution Approach 1:
The robot pre-calculates multiple patrol routes and identifies high-priority security zones before deployment. Security priorities, restricted areas, and patrol patterns are pre-configured based on building layouts and security protocols. This preliminary preparation enables the robot to make faster autonomous decisions during patrols without requiring complex real-time calculations, thereby improving productivity while managing algorithmic complexity.
Solution Approach 2:
The navigation system continuously receives feedback from sensors about real-time conditions such as detected security risks, obstacles, and changing environmental factors. This feedback loop allows the robot to dynamically adjust its route selection based on actual conditions while comparing against pre-established security priorities. The feedback mechanism simplifies decision-making by using established criteria rather than requiring complex autonomous judgment algorithms.
Data Source
AI summary
A mobile robot is configured for operation in a commercial or industrial setting, such as an office building or retail store. The robot can patrol one or more routes within a building, and can detect violations of security policies by objects, building infrastructure and security systems, or individuals. In response to the detected violations, the robot can perform one or more security operations. The robot can include a removable fabric panel, enabling sensors within the robot body to capture signals that propagate through the fabric. In addition, the robot can scan RFID tags of objects within an area, for instance coupled to store inventory. Likewise, the robot can generate or update one or more semantic maps for use by the robot in navigating an area and for measuring compliance with security policies.