Robot-to-Robot Identification Using Local Multi-Sensor Authentication
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Solution Overview
Problem
As service robots operating in different trust domains increasingly interact for tasks like parcel delivery, there is a need for robots to identify and authenticate each other without relying on authoritative third-party services, ensuring secure and trusted exchanges of assets.
Innovation Solution
Robots are equipped with a software-based algorithm that processes sensory inputs from integrated sensors like LIDAR, cameras, audio sensors, and Bluetooth transceivers to generate unique identification information, combining multiple pseudo-unique characteristics to create an identity nearly impossible to spoof.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If robots use traditional authentication methods relying on authoritative third-party services, then security can be maintained within single trust domains, but robot-to-robot authentication across different trust domains cannot be achieved
Solution Approach 1:
The patent introduces a trust mediator component that enables authentication between robots from different trust domains without requiring direct connection to authoritative third-party services. The mediator uses sensor-derived identification information to establish trust relationships across domain boundaries, resolving the contradiction between achieving cross-domain authentication and maintaining system simplicity.
Solution Approach 2:
The patent implements self-service authentication where robots autonomously generate and verify identification information using their own sensors (LIDAR, cameras, audio sensors, Bluetooth). This eliminates dependency on external authentication services for cross-domain interactions, enabling robots to independently authenticate each other while maintaining security.
2Reliability
If robots combine multiple sensor inputs to generate unique identification information, then authentication security is improved, but processing complexity and computational requirements increase
Solution Approach 1:
The patent segments the authentication process into distinct sensor modules (LIDAR processor, camera processor, audio sensor processor, Bluetooth processor), each independently generating identification information from its respective input. This modular segmentation reduces processing complexity by allowing parallel, independent processing of each sensor type while maintaining the security benefits of multi-sensor fusion.
Solution Approach 2:
The patent implements a weighted voting mechanism where not all sensor inputs require unanimous agreement for authentication. Instead, a threshold number of sensors meeting their individual confidence thresholds is sufficient, reducing computational complexity while maintaining high security through the redundancy of multiple independent verification channels.
3Productivity
If robots autonomously perform identification and authentication without human supervision, then operational efficiency is improved, but the risk of authentication errors or spoofing increases
Solution Approach 1:
The patent implements feedback mechanisms where each sensor processor provides confidence level information about its identification results. The trust mediator aggregates this feedback and can request re-authentication or additional verification if confidence levels are insufficient, reducing authentication errors while maintaining autonomous operation and high efficiency.
Data Source
AI summary
Described herein is a technique that provides a first robot associated with a first trust domain to identify and authenticate a second robot associated with a second trust domain. The identification and authentication technique described herein is based on a robot processing a variety of input signals obtained via sensors, in order to generate robot identification information that can be compared with known or trusted information. Advantageously, the identification technique occurs locally, for example, at the robot and at the location of the robot-to-robot interaction, eliminating any requirement for communicating with an authoritative remote or cloud-based service, at the time and place of the robot-to-robot interaction.