Sameer Prabhu / MathWorks Inc.

全球進行機器人研發的人員和工程師，現在都普遍利用MATLAB與Simulink設計並調整有關感知、規劃和控制之演算法；建立真實世界系統的模型以及自動產生程式碼—且全部都在同一個軟體環境執行。在這段演講，你將了解如何開發具有多個感測器、需要持續進行規畫及決策、並且必須符合控制和動作要求的複雜自主系統。模型化基礎設計(Model-Based Design)是一個能夠採用這些相互關聯的科技，並且讓它們無間合作的途徑。它以使用系統模型貫穿整個開發流程，包含設計、分析、模擬、自動產生程式碼、驗證等等。藉由一窺工業自動化的範例，可以看到深度學習等感知技術可以如何與工業機器手臂的動作規劃和控制演算法整合。

Robotics researchers and engineers use MATLAB® and Simulink® to design and tune algorithms for perception, planning, and controls; model real-world systems; and automatically generate code—all from one software environment. In this presentation, you learn how to develop autonomous systems that are complex with multiple sensors, need continuous planning and decision making, as well as have controls and motion requirements. An approach to adopt these interconnected technologies and make them work seamlessly is Model-Based Design. It centers on the use of system models throughout the development process for design, analysis, simulation, automatic code generation, and verification. Through the lens of an industrial automation example, see how techniques in perception, such as deep learning, can be integrated with algorithms for motion planning and control of a commercial robotic arm.