d2rds2

d2rds2, or Data-to-robot Decision System version 2, is a modular software framework designed to coordinate sensing, reasoning, planning, and action across distributed robotics and automation environments. It provides a common runtime, a declarative task-graph language, and pluggable components that can be composed to implement data-driven control loops. The second generation emphasizes interoperability, scalability, and real-time performance, and is intended for research labs, industrial pilots, and product deployments.

Architecture: d2rds2 adopts a layered, service-oriented architecture. The data layer collects sensor inputs and logs events; the decision engine applies rules, statistical models, or learned policies to determine goals; the planner constructs task sequences; the executor drives actuators and interfaces with controllers. A telemetry layer records provenance and metrics. Communication relies on standard protocols such as MQTT, gRPC, and REST, with a common schema for events and commands. The framework supports containerized deployment and a microservices model, enabling scaling across multiple machines.

Key features: real-time event processing, support for declarative task graphs, integration hooks for ML models, fault detection and isolation, time synchronization, sandboxed execution environments, and a simulation mode for testing. Security and access control are built in, with role-based permissions and audit trails.

History and ecosystem: d2rds2 evolved from earlier prototypes used in collaborative robotics projects. The first release introduced core data flows and planning; the 2.x series added better interoperability, a library of connectors to sensors and actuators, and improved tooling for visualization and debugging. It is released under a permissive open-source license and has an active community of implementers and researchers.

Applications and limitations: The framework is used for research in robot autonomy, warehouse automation, and field robotics pilots. It emphasizes openness and extensibility, but integration can require domain-specific adapters and careful configuration to meet real-time requirements. See also: robotics software frameworks, data-driven control, task graphs.