Static Timing Orchestration for Tree-Structured Robot Control Firmware

2026-08-05

AI Summary

This work addresses the control performance limitations in tree-structured robotic systems caused by hierarchical data dependencies that introduce latency from perception to decision-making. To mitigate this, the authors propose FineMote, a novel framework that introduces, for the first time, a static scheduling mechanism tailored to tree-based robot models. FineMote objectifies heterogeneous low-level control logic and determines execution order statically at compile time based on the device tree, enabling low-overhead scheduling. The approach rigorously enforces deadline and priority constraints and derives a theoretical upper bound on intra-tree decision latency. Experimental evaluation on a physical robotic platform demonstrates substantial improvements in timing behavior and runtime responsiveness, confirming the framework’s effectiveness and practicality.

Abstract

As robotic systems become increasingly complex, generating control firmware from structural description files has emerged as a promising paradigm for reducing development complexity and improving maintainability. Existing robot description formats naturally represent robotic systems as hierarchical tree structures, where devices are recursively composed into functional subsystems and eventually into the complete robot. However, such tree-structured organization also introduces structured data dependencies that affect perception-to-decision latency and, consequently, control performance. In this paper, we propose FineMote, a control firmware generation framework with a scheduling mechanism tailored for tree-structured device models. The framework objectifies heterogeneous low-level control logic and exposes unified scheduling units and execution entry points. Based on the resulting object hierarchy, the scheduling mechanism exploits compile-time information to statically determine execution order with minimal runtime overhead. We prove that the proposed mechanism satisfies deadline and precedence constraints, and further derive an upper bound on intra-tree decision latency. We implement the proposed framework and evaluate it on real robotic control platforms. The experimental results show improved timing behavior and runtime responsiveness, demonstrating the practical effectiveness of the proposed design.

Problem

• tree-structured robot control
• data dependencies
• perception-to-decision latency
• control performance
• firmware generation

Innovation

• Static Scheduling
• Tree-Structured Control
• Firmware Generation
• Real-Time Robotics
• Compile-Time Orchestration