11.1 Scaling Encrypted Job Workflows

Building Roborus requires solving cutting-edge technical challenges at the intersection of robotics, AI, and Web3 privacy. Unlike traditional marketplaces or robotics platforms, Roborus must combine encrypted workflows, verifiable proofs, and real-world deployments in a seamless and scalable way. This section outlines the core R&D areas critical for long-term success.

Challenge

Encrypted jobs and results ensure privacy, but encryption/decryption workflows add computational overhead. Scaling to thousands of jobs simultaneously requires efficient cryptographic pipelines.

Focus Areas

• Optimizing encryption libraries for robotics data (logs, maps, video streams).

• Leveraging hybrid approaches: lightweight encryption for telemetry, heavy encryption for sensitive artifacts.

• Parallel job handling using distributed coordination nodes.

R&D Direction

Build a privacy-preserving job scheduler that dynamically balances encryption security with processing efficiency.