Mobile Robot Latency Control Using Virtual Environmental Models
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Solution Overview
Problem
The adoption of robots in commercial and industrial settings, particularly in environments requiring frequent human-robot interactions, is hindered by the lack of technologies that enable effective communication and operation with building infrastructure and efficient performance of tasks such as security, inventory management, and navigation.
Innovation Solution
A mobile robot system that integrates wireless communication, sensors, and cameras to interact with elevator systems, perform inventory operations, and navigate through environments, while also being capable of autonomous adjustments to ensure safety and security by updating virtual models and detecting changes in the environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the mobile robot operates autonomously in commercial and industrial settings, then operational efficiency and task performance are improved, but the ability to respond to real-time human instructions and environmental changes deteriorates due to communication latency
Solution Approach 1:
The robot performs preliminary actions by autonomously executing tasks based on pre-generated virtual models of the environment. The system prepares and processes environmental data in advance, allowing the robot to operate efficiently without waiting for real-time human instructions for every action.
Solution Approach 2:
The system implements feedback mechanisms where the robot continuously updates the virtual model with real sensor data and compares it against the expected environment. When discrepancies are detected (indicating environmental changes), the system requests updated instructions from the human operator, ensuring safety while maintaining autonomous operation.
2Reliability
If the robot communicates frequently with the human operator for real-time instructions, then safety and environmental awareness are improved, but communication latency and response time deteriorate
Solution Approach 1:
The system creates and maintains a virtual model (copy) of the physical environment that the robot can query and navigate using without requiring continuous real-time communication. This virtual representation allows the robot to make decisions based on environmental data without waiting for human operator responses.
Solution Approach 2:
Environmental data and virtual models are prepared and updated in advance whenever changes are detected. The system proactively sends updated environmental information to the robot before human operators need to issue new instructions, reducing the need for frequent real-time communication.
3Reliability
If the robot autonomously detects and responds to environmental changes, then safety violation prevention is improved, but dependency on real-time human instructions is reduced causing potential safety gaps
Solution Approach 1:
The robot performs self-service by autonomously detecting environmental changes through its sensors and comparing them against the virtual model. When changes are detected, the robot independently determines appropriate safety responses and executes them without requiring human operator intervention, while still maintaining the ability to seek human guidance when needed.
Solution Approach 2:
The system implements a feedback loop where the robot continuously monitors environmental conditions, compares them with the virtual model, and automatically requests updated instructions from the human operator when discrepancies are found. This ensures human oversight is maintained while enabling autonomous safety responses.
4Productivity
If the robot uses virtual models for navigation and task execution, then operational autonomy and efficiency are improved, but accuracy in representing real-time environmental conditions deteriorates
Solution Approach 1:
The virtual model is created and prepared in advance based on environmental scans and data collection. The robot uses this pre-generated model for navigation and task planning, allowing autonomous operation without requiring real-time model updates for every action.
Solution Approach 2:
The system continuously validates the virtual model against actual sensor data from the environment. When discrepancies are detected between the virtual model and real-world conditions, the system triggers model updates and requests new environmental scans, ensuring the virtual representation remains accurate enough for safe autonomous operation.
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.