Robot Safety Zone Classification for Human-Robot Workspaces
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Solution Overview
Problem
In environments where humans and robots coexist, such as warehouses, existing safety systems fail to dynamically adjust safety modes based on the presence of human and robotic actors, leading to inefficiencies and potential safety risks due to fixed speed settings and lack of real-time safety area classification.
Innovation Solution
A safety system that employs a server to receive data from various sensors to dynamically change safety regions and modes by classifying areas as high, medium, or low safety based on actor types, using RFID, cameras, and other sensors to adjust speed and safety protocols accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If fixed speed settings are used in robotic devices, then device complexity is reduced, but productivity decreases due to inability to dynamically adjust speed based on environment
Solution Approach 1:
The patent implements dynamic speed adjustment by transitioning from fixed speed settings to variable speed control based on real-time environmental conditions. The robotic device continuously monitors its surroundings using sensors and dynamically adjusts its speed according to the detected safety classification of areas, enabling optimal productivity while maintaining safety.
Solution Approach 2:
The system employs feedback mechanisms where sensor data about the environment (human presence, robotic actor locations) is continuously fed back to the control system. This feedback loop enables the robotic device to adjust its speed and behavior in real-time based on the current safety classification, resolving the contradiction between fixed simplicity and dynamic efficiency.
2Reliability
If high safety modes are always active, then safety is improved, but productivity decreases due to restricted movement and speed limitations
Solution Approach 1:
The patent applies local quality by implementing spatially differentiated safety zones with varying safety classifications (low, medium, high). Instead of uniformly applying high safety modes throughout the entire environment, the system classifies specific areas based on their risk levels and applies appropriate safety restrictions only where necessary, allowing robotic devices to move freely in low-risk areas while maintaining strict safety protocols in high-risk zones.
Solution Approach 2:
The environment is segmented into multiple safety zones with different classification levels. This segmentation allows the system to apply tailored safety measures to each zone rather than a blanket approach, enabling robotic devices to operate at full efficiency in safe zones while implementing speed restrictions only in zones where human actors or other robotic devices are present.
3Adaptability or versatility
If real-time sensor data processing is implemented, then adaptability is improved, but device complexity increases due to additional sensors and processing requirements
Solution Approach 1:
The patent implements multi-functionality by designing a centralized server that handles multiple tasks: receiving data from various sensor types (RFID, cameras, presence sensors), processing this data to determine safety classifications, and communicating with multiple robotic devices. This universal server architecture consolidates the complexity into a single system rather than distributing it across multiple robotic devices, reducing individual device complexity while maintaining high adaptability.
Solution Approach 2:
The server acts as an intermediary between the sensors and the robotic devices. Instead of requiring each robotic device to directly process sensor data and make safety decisions, the server receives all sensor inputs, performs the complex processing and classification, then provides simplified guidance to the robotic devices. This intermediary approach isolates the complexity in the server while keeping robotic devices relatively simple.
Data Source
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AI summary
Systems and methods are provided for specifying safety rules for robotic devices. A computing device can determine information about any actors present within a predetermined area of an environment. The computing device can determine a safety classification for the predetermined area based on the information. The safety classification can include: a low safety classification if the information indicates zero actors are present within the predetermined area, a medium safety classification if the information indicates any actors are present within the predetermined area all are of a predetermined first type, and a high safety classification if the information indicates at least one actor present within the predetermined area is of a predetermined second type. After determining the safety classification for the predetermined area, the computing device can provide a safety rule for operating within the predetermined area to a robotic device operating in the environment.