HaRD-OS Dynamic Robot Task Routing
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Solution Overview
Problem
Robots face challenges in uncontrolled environments due to perception issues, particularly in manipulating objects with varying forms and locations, and require improved security and fault tolerance to effectively assist the elderly and disabled in everyday tasks.
Innovation Solution
The Human and Robot Distributed Operating System (HaRD-OS) dynamically connects human operators and algorithms with robots, allowing for efficient task allocation, security, and fault handling by selecting the best human or algorithm for each task, enabling robots to operate as extensions of humans and preventing unauthorized access or errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If robots operate autonomously in uncontrolled environments, then productivity increases, but perception accuracy deteriorates due to varying object forms, locations, and visual abnormalities
Solution Approach 1:
The patent introduces an intermediary perceptual system that bridges the gap between robot sensors and environment understanding. This system uses multiple sensors (LIDAR, cameras, depth sensors) and processing algorithms to create a robust representation of objects despite varying forms, locations, and visual abnormalities, enabling accurate perception in uncontrolled environments while maintaining autonomous productivity
2Ease of operation
If robots are given full autonomy to perform tasks, then ease of operation improves, but reliability deteriorates due to security vulnerabilities and fault tolerance issues
Solution Approach 1:
The patent implements beforehand cushioning by incorporating security protocols and fault tolerance mechanisms before autonomous operations begin. This includes authentication systems to verify robot identities, authorization frameworks to control access levels, and monitoring systems to detect and respond to faults proactively, ensuring reliable autonomous operation without compromising security
Solution Approach 2:
The patent employs feedback mechanisms where the robot's autonomous actions are continuously monitored and evaluated. Security events, perceptual uncertainties, and operational faults trigger feedback loops that adjust robot behavior, request human intervention when needed, or switch to safer operational modes, maintaining both ease of operation and reliability
3Measurement precision
If multiple sensors and algorithms are integrated to improve perception, then measurement precision improves, but device complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the complex perceptual system into modular sensor units and processing algorithms. Each sensor (LIDAR, camera, depth sensor) operates as an independent module with specialized processing, allowing the system to achieve high measurement precision through coordinated multi-sensor fusion while managing device complexity through modular architecture and standardized interfaces
Data Source
AI summary
Some embodiments provide a human and robot distributed operating system (HaRD-OS). The HaRD-OS efficiently and dynamically connects different human operators and algorithms to multiple remotely deployed robots based on the task(s) that the robots are to complete. Some embodiments facilitate an action/perception loop between the operators, algorithms and robots by routing tasks between human operators or algorithms based on various routing polices including operator familiarity, aptitude, access rights, end user preference, time zones, costs, efficiency, latency, privacy concerns, etc. In the event of a fault, some embodiments route to the best operator or algorithm that is able to handle the particular fault with the required privileges. Some embodiments secure task guarantees to be completed at particular times, priorities or costs.