Systems & Modules
MindGrid provides a modular, scalable, and hybrid architecture for robotics intelligence, designed to work across diverse hardware platforms while supporting real-time operation, safety, and observability. The architecture integrates open-source modules, premium APIs, pipelines, and deployment layers, allowing a unified intelligence layer to power humanoids, drones, robotic arms, and mobile bases.
System Overview
The MindGrid architecture can be understood as a multi-layered intelligence pipeline:
Sensors → Edge Runtime (OSS) → Gateway → Premium APIs → Planner/Controller → Actuators
↑ ↓
└--------------- Feedback Loops -------------┘Flow Explanation:
Sensors: Capture camera frames, lidar, IMU, audio, or telemetry from any robot body.
Edge Runtime (OSS): Lightweight models (mindgrid-smolVLM, early LLM, TTS/STT) process data locally for low-latency tasks.
Gateway: Manages authentication, quotas, telemetry, and secure routing to cloud APIs.
Premium APIs: Handle complex perception, reasoning, and high-fidelity TTS tasks.
Planner/Controller: Translates high-level decisions into trajectories, manipulator commands, and motion actions.
Actuators: Robot motors, grippers, or effectors execute planned actions.
Feedback Loops: Continuous state estimation, error detection, and optional human-in-the-loop intervention.
Modular Intelligence Components
Each module in the MindGrid architecture is independent but interoperable, allowing flexible pipelines:
Vision Systems: Object detection, scene understanding, multi-object tracking.
LLM Reasoning Modules: Task planning, tool use, memory management, exception handling.
Speech Interfaces (TTS/STT): Voice recognition, command parsing, expressive speech synthesis.
Motion & Control Primitives: Navigation, grasping, trajectory generation, ROS2 actions.
Developer APIs & SDKs: Unified endpoints for constructing pipelines and connecting modules.
Evaluation & Safety Tools: Regression tests, benchmarks, and monitoring systems for reliability and safety.
Last updated