Multi-Robot Mission Orchestration
Nov 6, 2026
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1 min read
We are developing a mission-orchestration system for multiple robots executing concurrent tasks in data centers. Robot availability, task priorities, resource constraints, and operating conditions change continuously, creating a dynamic, non-convex scheduling problem.
Our approach uses deep reinforcement learning to optimize mission allocation and scheduling across the fleet.
Authors
Senior Principal Applied Scientist
I lead applied research and engineering at the intersection of robotics,
reinforcement learning, agentic AI, and efficient AI systems. My work spans
embodied intelligence, large-scale model training and reasoning, inference
optimization, and deploying efficient models from cloud infrastructure to
edge devices.