Quickly troubleshoot robots and drones by asking targeted questions about performance, errors,
Open-source web-based diagnostic assistant for robotics; a client-server web app with a chat-like interface that analyzes robot telemetry and logs (e.g., ROS/ROS2 topics, run histories) to answer troubleshooting questions.
2025-08-27
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Highlight 1
Uses a chat-style interface to simplify complex diagnostics, making it easier for operators to ask targeted questions without deep tool-specific knowledge.
Highlight 2
Supports topic latency analysis and extraction of errors/warnings, enabling quick identification of performance bottlenecks and problematic runs.
Highlight 3
Open-source and customizable, allowing teams to adapt the tool to their specific robotics stack and data sources.
Improvement 1
Improve onboarding and documentation to help new users install, configure data sources, and start running queries faster.
Improvement 2
Expand integrations with common robotics ecosystems (e.g., ROS/ROS2, MAVLink) and provide ready-made connectors or adapters.
Improvement 3
Enhance UX with guided workflows, example queries, dashboards, and exportability (e.g., report generation, CSV/JSON export).
Product Functionality
Add ROS1/ROS2 and MAVLink connectors, enable dashboards for key metrics (latency, latency distribution, error frequency), and support exporting diagnostics as reports. Consider adding anomaly detection and alerting for abnormal message latencies or frequent errors.
UI & UX
Create guided onboarding with sample queries, templates, and tooltips. Introduce a command palette for quick access to common actions, improve visual consistency, and add a responsive design for tablet/desktop. Provide a dark mode option and keyboard navigation for power users.
SEO or Marketing
Publish a dedicated documentation site and tutorials about robotics troubleshooting with Bagel. Use SEO-friendly pages focusing on keywords like 'robot diagnostics', 'drone troubleshooting', 'ROS topic latency', and 'robot run analysis'. Maintain an up-to-date README with installation steps, use cases, and API references. Add structured data (schema.org) for better indexing and visibility on search engines.
MultiLanguage Support
Add internationalization (i18n) support to reach non-English-speaking users. Provide translated UI strings, documentation, and example queries. Consider community-driven translations and an in-app language switcher.
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What is Bagel and what problem does it solve?
Bagel is an open-source web-based diagnostic assistant for robotics. It lets teams query telemetry and log data about robot runs using natural language to quickly identify issues like latency, errors, warnings, and events (e.g., hard landings). It aims to streamline troubleshooting and speed up root-cause analysis.
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How do I get started with Bagel?
Clone the repository from GitHub, follow the README for installation and setup steps, install dependencies, and run the app locally or deploy it in your environment. You’ll then configure your data sources (telemetry/logs) and begin asking diagnostic questions.
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What data sources and questions does Bagel support?
Bagel analyzes robot telemetry and run data, including topic activity, latency, and logged errors/warnings. You can ask questions like whether a drone had a hard landing, what the latest message latency was on a topic, or which errors and warnings occurred during a specific run.