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Eclipse Muto
Autonomous driving and connectivity are cornerstones of the next generation of mobility. Users expect mobility experience to be personal, seamlessly integrated, connected and with demand services that can adapt to their immediate needs. These systems demand immense computing power in order to mimic the adaptivity and the awareness of a human driver under different driving circumstances and context variations. Contextual adaptivity requires a system to make sense of large volumes of rich & continuous data coming from the devices, the user behavior and the environment.
Many solutions use hardwired, closed & proprietary software with often unexplainable built-in biases. Robot Operating System (ROS) allows a modular system to be designed as a fully distributed computation, so different functional modules (i.e. sensing, perception, decision, planning, actuation, etc) can act together as a single autonomous vehicle.
A challenge with a typical ROS based hardwired solution is that the components (nodes, a network of interconnected computational and executable units) constituting the system are deployed into an environment to fulfill a certain concern with a specific mission plan, and they are not typically designed or implemented to react and to adapt changing requirements in the environment. A major difficulty that prevails for any adaptive system is being able to update the system without compromising its mission, plan, safety and security while it is active because the damages could be substantial.
Eclipse Muto provides an adaptive framework and a runtime platform for dynamically composable model-driven ROS software stacks on autonomous vehicles and robots in general.
Eclipse Muto introduces the concept of a lightweight model for ROS software stacks, which in its simplest form is a model for the system of connected ROS nodes and the context for which it is applicable. The Muto Agent and Muto Composer are ROS based runtimes designed to run on edge devices (i.e. AVs). Muto Dashboard is an extensible Web/Mobile application for centralized management of edge devices and Muto stacks deployed on these devices. Muto Composer runtime can introspect and change (i.e launch, stop, restart, configure, etc.) the network of distributed components running on a device using the Muto Stack definitions. Muto Agent allow remote management and monitoring of the devices and stacks and uses eclipse IoT technology such as Eclipse Ditto to define a digital twin for each device providing synchronous and asynchronous APIs and use the digital twin API to manage Muto stacks and ROS behavior.
The adaptive behavior is introduced by an extensible model where the context detection, stack rewriting, validation, constraint satisfaction, safety and security concerns can be offloaded to other modules (i.e proprietary systems). An example of such a module would be a remote control system where human operators determine the next configuration. A different implementation might use machine learning and scene detection to switch and transition to different stacks that are suitable to the current context.
Eclipse Muto provides an adaptive framework and a runtime platform for dynamically composable model-driven ROS software stacks. Eclipse Muto can be used to introspect, monitor and manipulate the actively running ROS graph (the network of ROS nodes).
Agent
Agent is a runtime ROS component (Node) acting as a transceiver between the edge device and the twin server (Eclipse Ditto). Agent acts as a gateway between the device and remote management capabilities with support for asynchronous communication capabilities via MQTT. It acts as a communication bridge between edge devices and their respective virtual twins. The main aspects of data transported by Agent are as follows:
Device Telemetry
Agent is capable of publishing data streams up to the Twin Server, such as data that streams in ROS topics. Stream of data mapped from edge device to virtual one, could represent instant telemetry information and/or any other device specific details. This kind of data is useful for monitoring devices and algorithmic parameters with adjustable-frequency updates. Data such as odometry, speed, localization, goal or any other drive and device related can be broadcasted via declarative models. This kind of fast paced, high frequency data moving up to digital twins is also read by Muto Dashboard to provide a graphical interface and an adequate representation of aforementioned data.
Command Relay
Agent relays commands from the twin server to Composer running on the edge device. This type of information may be related to the lifecycle of ROS nodes that constitute the software stack actively running on the edge device as well as the lifecycle actions (start, stop, update etc) that may trigger the composer to respond.
Composer
Composer is a runtime ROS component (Node) that is responsible for the life cycle of a stack; Composer uses various ROS packages and APIs to launch ROS Nodes defined by the software stacks. It can be thought of as a smart launch manager. Composer uses the stack information model and computes the delta between the current and the desired state of the ROS graph and manages the lifecycle of ROS nodes accordingly.
Dashboard
A simple extensible Web/Mobile application for centralized management of edge devices and software stacks. It provides a plugable micro front end architecture for extensibility and an exemplary view for managing edge devices and composable ROS stacks on these devices. It supports and uses Eclipse Ditto device twins technology (and therefore protocols such as MQTT and REST/HTTP) for managing ROS based devices. It is designed to be modular at architectural level to make it easy to extend for a multitude of ROS applications.
The dashboard provides the following functionalities:
- Node Viewer : A graphical visualization of the ROS computational network that represents the actively running ROS nodes of the current state. It displays the node-to-node and node-to-topic affiliations with introspection information ( name, subscriber, publisher etc.)
- Stack Panel
- List: An interface to list the stack models that describe the components of a software stack that complies with the information model stored in the twin server.
- Diff: An interface to describe the algebraic differences between two models in terms of nodes and node related parameters .
- Remote Control Actions: An interface to manage (start,stop, update) the lifecycle of the software stack on the edge device.
- ROS Controls: Dashboard provides a graphical UI for some of the common ROS cli commands.
LiveUI
Micro frontends is an architectural style where independently deliverable frontend applications are composed into a greater whole. Muto LiveUI has been developed for building any such extensible Web or Mobile apps, such as the Muto Dashboard.
LiveUI opts for run-time integration via JavaScript that is tightly integrated with popular Javascript frameworks such as React.js, Vue.js and integrates well with packaging and development tools such as npm, Webpack and Metro bundler. There is a cost to using distributed, micro service based architecture; there are more pieces, more repositories, more tools, more build/deploy pipelines, more servers, more domains, etc. We created LiveUI to help us manage some of these issues and improve the developers' experience using micro frontends. Live UI can be fully configurable to be integrated into many different devops processes and pipelines allowing many different custom project and repository layouts, test and quality tools. Development tooling and debugging experience is seamless with or without the inclusion of the container (parent) frontend.
Examples
We use/fork code and examples from open initiatives such as f1tenth.org Autonomous Vehicle System, a powerful and versatile open-source platform for autonomous systems research and education, and Autoware.org an open-source software stack for self-driving vehicles to demonstrate dynamically adaptive ROS stacks. These examples provide a common repository for learning and teaching ROS and adaptive AD capabilities.
Initial contribution includes code derived from other open-source projects please see the relevant section where we disclose these projects and their licenses.
Current industry practices for automotive software embrace proprietary and closed solutions. Many common building blocks are replicated within the industry. Open Source software such as the Robot Operating System (ROS) and Autoware demonstrate how the industry can benefit from Open Source. Eclipse Software Defined Vehicle can become a focal point for open technology and collaboration within which Muto can contribute to solving some of the harder questions about contextual and adaptive ROS software, and create opportunities for collaboration for innovative niche solutions and large scale implementations driven by OEMs and Industry leaders.
In future release, we plan to provide:
- Enhanced ROS/Ditto Twins integration
- Adaptivity plugins (i.e. remote-control)
- Mobile Extensions for LiveUI (react-native)
Initial contribution will be submitted before the end of Q2, 2022.
Initial code contribution will be organized under the following repositories:
- Core (for common models and utilities)
- Agent
- Composer
- Dashboard
- LiveUI
- Examples
The source code for Eclipse Muto is partially available in open source repositories (https://github.com/composiv and https://liveui.composiv.ai/ ) and internal private repositories (Agent, Composer, Dashboard). The runtime components target ROS runtimes, therefore use APIs and some code derived from the ROS repositories.
Composiv examples use/fork code from various f1tenth.org, autoware.org repositories and are subject to copyright and ownership of these repositories.
The following are some of the primary open-source, third party libraries that are relevant to Eclipse Muto:
- Robot Operating System (ROS)
- https://www.ros.org/
- https://github.com/ros
- Apache v2 (ROS2) and (ROS 1) BSD, MIT and other Various Licenses
- F1Tenth.org (MIT, BSD and other Various Licenses)
- https://github.com/f1tenth/f1tenth_system F1tenth System
- https://github.com/f1tenth/particle_filter Particle Filter (a fork from https://github.com/mit-racecar/particle_filter )
- https://github.com/f1tenth/f1tenth_simulator F1tenth Simulator
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