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Closing Latency Gap In Physical AI

March 22, 2023

2 min read

Key Takeaways

Latency poses safety risks in collaborative assembly cells.
Edge-first architectures can reduce latency.
Direct bridge from edge processor to robot controller is key.
Legacy PLCs create unacceptable bottlenecks.

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Strategic Implications

This shift towards edge-first architectures may indicate a significant change in how collaborative robots are designed, suggesting a focus on real-time safety and throughput. The use of localized real-time safety processors could enable more efficient and adaptive human-robot collaboration, which may lead to increased productivity and safety in manufacturing environments.

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What Happened

Why Edge-First Architectures Matter For Collaborative Robots

The Robot Report discusses the importance of closing the latency gap in physical AI for collaborative robots. According to Madhu Gaganam, founder and CEO of Cogniedge.ai, latency can pose significant safety risks in high-mix collaborative assembly cells. To address this, edge-first architectures that move AI inference to the edge and establish a direct bridge from the edge processor to the robot controller are necessary. This approach can enable real-time safety and throughput, making collaborative robots more efficient and adaptive. The article was first reported by The Robot Report.

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