Webinars
Building Smarter Robots: From AI Perception to Real-World Deployment
Originally Recorded June 11, 2026 | 1-2 PM ET
ABOUT THIS WEBINAR
As robotics systems become more intelligent, the challenge is no longer just enabling AI. Its integrating perception, compute, and control into systems that can reliably operate in the real world.
This webinar brings together NVIDIA, RealSense, and Advantech to explore how modern robotics platforms are solving the biggest challenges in deployment, from sensor fusion and real-time perception to scalable AI processing across edge and centralized systems.
We will examine how multi-modal AI and advanced vision technologies are enabling faster development and more reliable performance in AMRs, humanoid robotics, and intelligent automation systems. The discussion will also highlight how these architectures extend into more advanced applications such as medical robotics, where low latency, precision, and scalability are critical.
Attendees will hear directly from industry leaders on how integrated hardware and software ecosystems are accelerating time-to-market, reducing development complexity, and enabling scalable robotics deployments.
Key Takeaways:
- How to overcome key challenges in robotics deployment (perception, AI, and integration)
- Best practices for sensor fusion, real-time AI, and system architecture
- How ecosystem partnerships accelerate robotics development and deployment
Exclusive Sponsor
Advantech’s corporate vision is to enable an intelligent planet. The company is a global leader in the fields of IoT intelligent systems and embedded platforms. To embrace the trends of IoT, big data, and artificial intelligence, Advantech promotes IoT hardware and software solutions with the Edge Intelligence WISE-PaaS core to assist business partners and clients in connecting their industrial chains. Advantech is also working with business partners to co-create business ecosystems that accelerate the goal of industrial intelligence.
Chris Matthieu, VP, Developer Ecosystem, RealSense
Chris Matthieu is a serial entrepreneur and active developer who has built and sold five emerging tech companies in the areas of communications, IoT, and decentralized supercomputing. He currently serves as the VP, Developer Ecosystem for RealSense, where he focuses on AI, robotics, and stereo depth technologies. Chris is a frequent speaker at robotics and emerging technology conferences.
Daniel Bravo, Product Manager, Advantech
Daniel Bravo is a Product Manager at Advantech, specializing in AI Ready and Edge AI Solutions, utilizing over thirty years of experience in the software industry to bridge the AI gap between software and hardware, Daniel facilitates the complete AI Solution for the customer that allows them to go to market faster regardless of their in-house AI expertise or lack there of. With the ultimate goal of reducing the barriers to entry into Edge AI, Daniel specializes in simplifying solutions to otherwise complex and difficult problems, allowing customers to step into the world of AI with confidence.
Eunice Chen, Product Manager, Advantech
Eunice Chen is a Product Manager of Autonomous Systems & Robotics, and Arm Computing in Advantech, with 10 years of experiences in product management for industrial PC industry. She focuses on vertical markets business development for autonomous systems and robotics, including warehouse AMR, autonomous forklift, humanoid, and drones. She works with ecosystem partners like sensor and camera providers, silicon partners like NVIDIA, Qualcomm, NXP and Intel, and operating system providers like Canonical, QNX and Microsoft.
Jay Carlson, Sr. Product Manager, NVIDIA
Jay Carlson is cross-disciplinary engineering leader with experience in robotics, embedded systems, imaging technologies, and edge AI platforms. He previously helped develop the FDA-cleared MIRA Robotic-Assisted Surgery System at Virtual Incision, leading electrical architecture and cross-functional engineering efforts. His background spans medical robotics, IoT, AI startups, high-speed imaging, embedded Linux, CUDA image processing, and real-time video systems. He brings a practical perspective on how advanced compute and vision technologies can help accelerate robotics development from concept to deployment.
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