Lodestar: An Integrated Embedded Real-Time Control Engine

TL;DR

Lodestar is a comprehensive real-time control engine that simplifies complex control system development through a functional block diagram approach, supporting rapid prototyping, execution, and integration with hardware and software.

Contribution

It introduces a unified framework for control, signal processing, and vision routines that enables real-time performance and easy translation to source code for embedded systems.

Findings

Successfully implemented real-time torque control for a robotic arm.

Developed a novel autofocus algorithm for thermography-based localization.

Demonstrated Lodestar's ease of use and integration in various control and simulation scenarios.

Abstract

In this work we present Lodestar, an integrated engine for rapid real-time control system development. Using a functional block diagram paradigm, Lodestar allows for complex multi-disciplinary control software design, while automatically resolving execution order, circular data-dependencies, and networking. In particular, Lodestar presents a unified set of control, signal processing, and computer vision routines to users, which may be interfaced with external hardware and software packages using interoperable user-defined wrappers. Lodestar allows for user-defined block diagrams to be directly executed, or for them to be translated to overhead-free source code for integration in other programs. We demonstrate how our framework departs from approaches used in state-of-the-art simulation frameworks to enable real-time performance, and compare its capabilities to existing solutions in the realm of control software. To demonstrate the utility of Lodestar in real-time control systems design, we have applied Lodestar to implement two real-time torque-based controller for a robotic arm. In addition, we have developed a novel autofocus algorithm for use in thermography-based localization and parameter estimation in electrosurgery and other areas of robot-assisted surgery. We compare our algorithm design approach in Lodestar to a classical ground-up approach, showing that Lodestar considerably eases the design process. We also show how Lodestar can seamlessly interface with existing simulation and networking framework in a number of simulation examples.