Edge Teleoperation Failover Using AI-Learned Remote Control State
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Solution Overview
Problem
Current teleoperations infrastructures lack redundancy, compromising safety, reliability, and security due to direct peer-to-peer communication without backup systems and stateless communication.
Innovation Solution
Implementing an edge computing-based teleoperations service that includes geo-redundant remote-controlling devices, an anchor service, AI service, and state transfer service to manage switchover between active and backup devices, ensuring reliable communication and operation continuity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If direct peer-to-peer communication is used between remote-controlled device and remote-controlling device, then communication simplicity is improved, but reliability and security deteriorate due to lack of backup systems
Solution Approach 1:
An edge computing device is introduced as an intermediary between the remote-controlled device and remote-controlling devices. The edge computing device receives control inputs from remote-controlling devices, processes them, and transmits to the remote-controlled device. It also relays sensor data and media streams from the remote-controlled device to remote-controlling devices, thereby improving reliability while maintaining communication simplicity.
Solution Approach 2:
The edge computing device pre-establishes communication channels and maintains buffer queues for control inputs and sensor data before actual teleoperation occurs. This preliminary preparation ensures that when teleoperation is needed, reliable communication pathways are already in place, reducing latency and improving system reliability.
2Device complexity
If direct peer-to-peer communication is used, then system complexity is reduced, but safety and security are compromised due to lack of redundancy
Solution Approach 1:
The system implements redundant communication pathways and backup mechanisms in advance. The edge computing device maintains buffer queues for control inputs and sensor data, and can switch between multiple remote-controlling devices (active and backup). This beforehand preparation cushions against potential failures, improving safety without significantly increasing operational complexity.
Solution Approach 2:
The edge computing device creates and maintains copies of critical data (control inputs, sensor data, media streams) in buffer queues. These copies serve as backups that can be used if the primary communication channel fails, thereby improving safety and security while adding minimal complexity to the system architecture.
3Productivity
If stateless communication is used, then communication efficiency is improved, but reliability deteriorates due to lack of session management
Solution Approach 1:
The edge computing device implements feedback mechanisms by maintaining session states and buffer queues. It tracks the state of teleoperation sessions, manages active and backup remote-controlling devices, and ensures continuous data flow. This feedback loop improves communication reliability while maintaining efficiency through optimized data transmission.
Solution Approach 2:
The edge computing device performs multiple functions including relaying control inputs, transmitting sensor data, managing communication sessions, maintaining buffer queues, and coordinating between active and backup remote-controlling devices. This multi-functionality improves reliability by centralizing session management while maintaining communication efficiency through a single coordinated point.
4Reliability
If backup remote-controlling devices are implemented, then reliability is improved, but device complexity increases
Solution Approach 1:
The edge computing device serves as an intermediary that manages the complexity of coordinating multiple remote-controlling devices. It maintains session states, identifies active and backup devices, and handles switchover operations. This centralizes the complexity in a single device rather than distributing it across multiple remote-controlling devices, thereby improving reliability while keeping the overall system complexity manageable.
Solution Approach 2:
The edge computing device creates and manages copies of session states and communication channels for active and backup remote-controlling devices. This allows seamless failover by simply switching between pre-prepared copies rather than establishing new connections, improving reliability while minimizing the complexity increase from having multiple devices.
Data Source
AI summary
A method, a device, and a non-transitory storage medium are described in which an edge computing-based teleoperations service is provided. An edge network device may select an active and one or multiple backup remote-controlling devices in support of a teleoperations service session. The edge network device may include artificial intelligence to learn remote-controlling functions based on communications relayed between a remote-controlled device and the active remote-controlling device. The edge network device may use the learned remote-controlling functions during a failover procedure or other triggering network event.