Robotic Vehicle Theft Detection Using Trust Factors
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Solution Overview
Problem
Robotic vehicles, particularly unmanned aerial drones, are vulnerable to theft and unauthorized use due to their small size and autonomous operation, lacking effective methods to detect and respond to theft or unlawful operation.
Innovation Solution
A robotic vehicle processor evaluates unauthorized use indicia, such as SIM card changes, operator skills, and trust factors, to determine theft, and initiates recovery actions like escaping, hiding, or self-destruction, while providing misleading information to thieves.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If robotic vehicles operate autonomously without theft detection systems, then ease of operation is improved, but vulnerability to theft increases
Solution Approach 1:
The system performs preliminary actions by storing authorized operator identifiers and trust factor criteria before theft can occur. The processor continuously evaluates trust factors and compares current operator identification against stored authorized identifiers, preventing unauthorized operation before it can result in theft.
Solution Approach 2:
The system implements feedback by continuously monitoring operational parameters, evaluating trust factors, and comparing current state against stored authorized profiles. When unauthorized use is detected through failed authentication or suspicious behavior patterns, the system provides feedback by triggering countermeasures such as disabling controls or activating alarms.
2Object-affected harmful factors
If theft detection and response systems are implemented, then security against theft is improved, but device complexity increases
Solution Approach 1:
The processor utilizes existing multi-functional capabilities of the robotic vehicle's control system and communication hardware for theft detection. The same processor that controls vehicle operations also evaluates trust factors and detects unauthorized use, while existing communication transceivers serve both operational communication and theft reporting functions, avoiding additional dedicated hardware.
Solution Approach 2:
The system performs self-service by using the robotic vehicle's own existing sensors, processors, and communication systems to detect and respond to theft attempts. The vehicle's processor evaluates trust factors using data from its own operational sensors, and the vehicle's communication system reports theft to authorized operators, eliminating the need for separate dedicated theft detection hardware.
3Measurement precision
If multiple trust factors are evaluated for theft detection, then measurement precision of unauthorized use detection is improved, but computational requirements increase
Solution Approach 1:
The system applies partial action by evaluating trust factors in a prioritized sequence, starting with the most critical and computationally efficient factors such as operator identification authentication. Less critical factors are evaluated only if initial checks pass or when suspicion arises, reducing overall computational load while maintaining detection precision through layered evaluation.
Data Source
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AI summary
Various methods enable a processor of a robotic vehicle e.g. an aerial drone to determine when the robotic vehicle has been stolen so that a self-recovery operation may be performed. Determining whether the robotic vehicle has been stolen may include evaluating, by a processor of the robotic vehicle, unauthorized use indicia, and determining that the robotic vehicle is stolen in response to determining that unauthorized use indicia exceed a threshold. Evaluating unauthorized use indicia may include determining whether an Integrated Circuit Card Identifier of a Subscriber Identify Module matches a stored value, determining whether a paired controller is different from a usual controller, determining whether the operator's skill has changed, and evaluating one or more trust factors that are observable features of normal operation.