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Chapter 13: Multimodal Robotics (Vision + Language + Action)

Template

Fill in content from specs/001-physical-ai-book-specs/spec.md lines 1171-1248. Use Chapter 11 (11-voice-to-action.mdx) as formatting reference.

Overview​

TODO: Add overview paragraph introducing multimodal systems (spec.md lines 1173-1175)

Target Audience: Developers building end-to-end AI-driven robotic systems.

Learning Objectives​

By the end of this chapter, you will be able to:

  1. TODO: Add learning objective 1 from spec.md line 1179
  2. TODO: Add learning objective 2 from spec.md line 1180
  3. TODO: Add learning objective 3 from spec.md line 1181
  4. TODO: Add learning objective 4 from spec.md line 1182
  5. TODO: Add learning objective 5 from spec.md line 1183

Multimodal Integration Overview​

TODO: Explain multimodal integration (spec.md line 1187)

Mermaid Diagram TODO: Create VLA Pipeline diagram (spec.md line 1222)

TODO: Camera → Vision Model → Object Detections → LLM Reasoning → Action Plan → Robot Controller

Vision Models for Object Detection​

TODO: Explain vision models (spec.md line 1188)

  • Object detection (YOLO)
  • Segmentation (SAM)
  • Pose estimation

TODO: Add installation and usage commands (spec.md lines 1201-1218)

# TODO: Add commands from spec.md lines 1204-1217
# - Install YOLOv8
# - Run object detection
# - Publish detections to ROS 2
# - Call LLM for reasoning
# - Execute manipulation action

Vision-Language Models​

TODO: Explain vision-language models (spec.md line 1189)

  • CLIP
  • LLaVA
  • Understanding visual scenes via natural language

Example TODO: Add CLIP example (spec.md line 1198)

Integrating Vision with LLM Reasoning​

TODO: Add section on vision-LLM integration (spec.md line 1182)

Mermaid Diagram TODO: Create Multimodal Integration diagram (spec.md line 1223)

TODO: Show vision node, LLM node, action server, and data flow

Example TODO: Add "pick up the red cup" example (spec.md line 1196)

Action Execution with Manipulation Controllers​

TODO: Explain manipulation execution (spec.md line 1190)

  • MoveIt integration
  • Grasp planning
  • Motion planning

Mermaid Diagram TODO: Create Object Detection → Grasp Planning Flow (spec.md line 1224)

TODO: 2D bounding box → 3D pose estimation → grasp pose → MoveIt trajectory

End-to-End VLA Pipeline​

TODO: Explain complete pipeline (spec.md line 1191)

Example TODO: Add "move all toys to the box" example (spec.md line 1197)

Testing VLA in Simulation​

TODO: Add sim-to-real testing section (spec.md line 1192)

Mermaid Diagram TODO: Create Sim-to-Real Workflow (spec.md line 1225)

TODO: Develop in Isaac Sim → Train on synthetic data → Deploy to real robot

Practice Tasks​

Complete these exercises to master multimodal robotics:

Task 1: Install and Test YOLO​

TODO: Add task details from spec.md line 1229

Task 2: Create Vision Detection Node​

TODO: Add task details from spec.md line 1230

Task 3: Integrate Vision with LLM​

TODO: Add task details from spec.md line 1231

Task 4: Full VLA Pipeline in Simulation​

TODO: Add task details from spec.md line 1232

Summary​

TODO: Add summary points from spec.md lines 1236-1241:

  • Multimodal systems combine vision, language, action
  • Vision models for detection and localization
  • LLMs for reasoning
  • Manipulation controllers
  • End-to-end VLA pipelines
  • Isaac Sim testing

References​

Next Chapter: Chapter 14: System Architecture - Design modular, production-ready system architectures for humanoid robotics.