SOURCE-LINKED INTELLIGENCE

LEMCA: LLM-Guided Synthesis of Efficient Mode-Switching Control Architectures

arXiv · AI, language, vision and robotics · article · Sep 18, 2026 · UTC

Physical control tasks in the natural world, such as driving or object manipulation, frequently exhibit dramatic variations in sensory and compute complexity over time. Correspondingly, a natural resource-efficient choice for robot control is to dynamically switch between control modes with varying resource allocations. However, such "mode-switching controllers" (MSCs) have historically required laborious, expert-driven design and synthesis for each new task. Driven by these design difficulties, modern robotic control architectures often fall back to a wasteful "monolithic" one-size-fits-all s

Read original source ↗ Open in workspace

recordType

paper

region

Global