ROS 2

Rosbag2 is a ROS 2 tool for recording and playing back timestamped messages exchanged by robotics systems. It records all available topics or selected topics, can discover topics that appear during recording, and stores the data in a bag directory for later inspection or replay. It is available through the ROS 2 command-line interface as `ros2 bag`, with commands for recording, playback, conversion, information, listing, bursting, and reindexing; its recorder and player can also run as `rclcpp` components.

Dalaran is an Apache-2.0 robotics-focused observability and visualization stack for recording, replaying, and inspecting multimodal time-series data such as ROS 2 topics, LiDAR sweeps, camera streams, IMU readings, and TF transforms on a synchronized timeline. It is a hard fork of Rerun, uses an Arrow-backed columnar chunk store, renders synchronized 2D and 3D views, and exposes recorded data as dataframes for computation. The project supports Python, Rust, and C++ SDKs, a viewer and CLI, ROS 2 data, Rosbag 2 and MCAP replay, existing Rerun .rrd recordings, and Dalaran .dlr recording files with saved .dbl blueprints; recordings can be written to files or streamed to a viewer or remote catalog.

Rerun is an open-source SDK and data layer for recording, querying, visualizing, transforming, and streaming multimodal physical-robotics data. It ingests multi-rate data such as images, point clouds, transforms, time series, joint states, tensors, and video from robot logs, human-data rigs, simulation, and web video, using formats including MCAP, RRD, and LeRobot. Its built-in viewer synchronizes and renders the data in real time for episode scrubbing, sensor comparison, and live computer-vision pipelines; the same data can be queried with dataframes or SQL and streamed directly into training. Rerun is built in Rust on column-chunk storage designed for multi-rate physical data, with Python, Rust, and C++ SDKs and a separate Viewer binary for network streaming and RRD files. The repository describes the project as being in active development, with an evolving API and possible breaking changes.

ODS is a self-hosted local AI server stack developed by Osmantic for Linux, Windows with WSL2 and Docker Desktop, and Apple Silicon macOS. Its installers detect the host hardware, select an installable model, generate credentials, and launch a preconfigured stack containing local LLM inference, Open WebUI, a management dashboard, LiteLLM, embeddings, speech-to-text, text-to-speech, agents, n8n workflows, Qdrant-based RAG, search, ComfyUI image generation, and operational and privacy tools. Local mode is the default; cloud and hybrid modes can route through OpenAI, Anthropic, or Together APIs. The stack uses a bootstrap model so chat can begin while the hardware-selected full model downloads in the background. A manifest-based extension system discovers service folders and merges their Docker Compose definitions into the stack, while the `ods` CLI manages services, models, modes, configuration, presets, and lifecycle operations. The repository documents GPU and unified-memory paths for NVIDIA, AMD, Intel Arc, and Apple Silicon hardware, along with model selection, recovery, validation, and operator workflows. ODS is distributed as an Apache-2.0-licensed open-source repository and can be installed with shell or PowerShell installers. The repository identifies version 2.6.0 as its stable release and states that no cloud account or subscription is required for local operation.

OpenResearch is a local-first workspace for research agents and autoresearch, available as a desktop application and a macOS/Linux CLI. It turns Claude Code, Codex, or OpenCode into agents that can review literature, develop hypotheses, run experiments, and produce research artifacts. The workspace assigns independent agent sessions and isolated Git worktrees to parallel research directions. It tracks experiment variants in a Git-native experiment tree, archives each run against its recorded commit, and keeps logs, diffs, files, results, and artifacts tied to the work that produced them. Its autoresearch loop can propose an idea, modify code, launch an experiment, inspect evidence, and choose the next direction. The same committed source snapshot can run locally or through SSH, Slurm, Kubernetes, Ray, Hugging Face Jobs, Modal, Tinker, or managed OpenResearch compute. By default, projects and run data remain on the user's machine in a local SQLite store, with a browser dashboard served on localhost. An OpenResearch account is used for service-owned capabilities such as organizations and managed compute. The CLI also installs an OpenResearch skill into supported coding agents and provides commands for projects, runs, logs, experiments, discovery, and paper lookup.