Autonomous Robot Camera Certification for Latency and Throughput
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Solution Overview
Problem
The use of uncertified cameras in safety-critical applications like autonomous mobile robots is hindered by performance gaps, such as glitches due to latency, inadequate throughput, and minimalistic processing, which can lead to safety issues and increased costs when certified cameras are required for reliable navigation.
Innovation Solution
A system that includes a light source, such as an LED, is used to irradiate the field of view of a depth camera, with a processing system that monitors and calculates latency and throughput, ensuring the camera operates within safety-certified parameters, thereby enabling the use of non-certified cameras in safety-critical systems by simulating a certified camera's performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If uncertified cameras are used in autonomous robots, then cost is reduced, but reliability and safety are compromised due to latency, inadequate throughput, and processing glitches
Solution Approach 1:
A light source is introduced as an intermediary component between the uncertified camera and the environment. The light source actively illuminates the scene and enables real-time certification by providing a known reference signal that the processing system can use to verify camera performance metrics such as latency and throughput, thereby bridging the gap between uncertified hardware and safety requirements
Solution Approach 2:
The system implements feedback by continuously monitoring camera output and comparing it against expected performance parameters. The processing system analyzes the camera's response to the light source and adjusts or validates operation based on measured latency and throughput, creating a closed-loop system that ensures safety even with uncertified components
2Reliability
If certified safety camera systems are used, then reliability and safety are improved, but cost increases significantly
Solution Approach 1:
The patent replaces expensive certified camera systems with cheaper uncertified cameras that can be rapidly replaced or recalibrated. The use of inexpensive cameras combined with software-based certification allows the system to achieve safety requirements without the high hardware costs of certified components
Solution Approach 2:
The system changes the operational parameters of the uncertified camera through active illumination and controlled testing protocols. By modifying how the camera is used (with light source activation and real-time performance monitoring) rather than relying on expensive hardware certification, the system achieves safety-equivalent performance at lower cost
3Reliability
If certified safety camera systems are used, then safety is improved, but device complexity and physical volume increase
Solution Approach 1:
The light source and camera are merged into a single integrated unit mounted on the robot. This combination eliminates the need for separate certification hardware and reduces overall system complexity while maintaining safety through the integrated certification capability
Solution Approach 2:
The uncertified camera system is given multiple functions: it serves both as the primary navigation sensor and as a subject of real-time certification. The same camera that navigates the robot also undergoes continuous safety verification through the light source interaction, eliminating the need for dedicated certified hardware
4Reliability
If certified safety camera systems are used, then safety is improved, but data processing speed and volume requirements increase
Solution Approach 1:
The light source is activated in advance to establish a known reference state before navigation begins. This preliminary action allows the processing system to pre-calculate expected camera responses and latency parameters, reducing the computational burden during real-time navigation while maintaining safety verification
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows the use of uncertified cameras in autonomous robots by ensuring real-time data reliability and safety, reducing costs associated with certified cameras while maintaining safety standards, by assessing and maintaining acceptable latency and throughput.
Implementation Method 1
at least one light source resident on the robot body proximate to the sensing camera such that the at least one light source is capable of at least partially irradiating a field of view (FoV) of the sensing camera
Data Source
AI summary
An apparatus, system and method of for certifying a sensor that at least partially navigates an autonomous mobile robot. The apparatus may include at least a robot body; at least one light source resident on the robot body proximate to the sensing camera such that the at least one light source is capable of at least partially irradiating a field of view (FoV) of the sensing camera, wherein the at least one light source has characteristics substantially mated to the sensing camera; and at least one processing system that provides the at least partial navigation. The at least one processing system may execute the steps of: actuating the at least one light source at a predetermined time and for a predetermined duration; monitoring data from the sensing camera for confirmation of the actuating; calculating at least one of the latency, throughput, and reactivity of the sensing camera based on the monitoring; and at least partially navigating based on the calculating.