Enabling Robotic Independence Through Machine Vision

Gregory Hitz, Ph.D.  |  Managing Director  |  Sevensense by ABB

Human vision is a corner stone in our ability to sense and understand our environment; one that we rely on in almost all daily tasks. Gregory Hitz’s presentation will highlight how enabling machines to see their environments is a fundamental building block for making robots more independent, more versatile, and ultimately part of a physical AI world.

Gregory Hitz, ABB

Machine Vision’s Shifting Value: Why System Vendors Still Matter
in the Age of AI and Commodity Sensors

Tom Brennan  |  President and Founder  |  Artemis Vision

The machine vision market is experiencing an unusual split. Despite steady year‑over‑year growth in system sales, public market valuations tell a different story. Several major machine vision companies have seen their stock prices decline by 21% to 78% over the past five years, even as leading AI companies have surged more than 100%. This divergence suggests that the industry is separating into two distinct segments. On one side are proven, production‑grade systems—fixed installations that deliver clear value and continue to sell. On the other is an emerging “no‑man’s‑land” defined by commoditized sensors and a small number of dominant AI players, leaving many traditional vendors squeezed in the middle. This presentation explores what the next-generation machine vision landscape may look like as these forces reshape the industry.

Tom Brennan

Evaluating Structured Light, Time of Flight, Stereo, and Laser Triangulation for 3D Vision Systems

Daniel L. Lau, Ph.D.  |  Director of Graduate Studies  |  University of Kentucky in Lexington

In this keynote, Dr. Daniel Lau will deliver a clear, practical comparison of the major 3D imaging technologies used in industrial machine vision. He will examine structured‑light systems, time‑of‑flight cameras, stereo vision, and laser triangulation—outlining how each method captures 3D data and the implications for accuracy, speed, surface coverage, and environmental robustness.

For each technology, he’ll break down core operating principles, critical performance parameters, typical use cases in automation and inspection, and key integration factors such as calibration, lighting, processing demands, and mechanical constraints.

Attendees will gain a grounded understanding of the strengths and limitations of each approach to help them confidently evaluate, specify, and deploy the right 3D vision solution for their application requirements.

Dr. Daniel Lau

Integrated Quality 4.0: Building End‑to‑End Data Traceability Into Vision Systems

Prashant Shah  |  Chief Operating Officer  |  Lincode Labs

Next‑generation inspection systems don’t just classify defects—they record full visual logs, timestamps, and identifiers for comprehensive traceability, enabling analytics, compliance, and root‑cause analysis.

Prashant Shah

Roundtable: Will Humanoids Kill Traditional Machine Vision Systems?

Ronald Müller  |  Managing Director  |  Vision Markets

Sebastien Dignard  |  CEO  |  Macnica Americas and EMEA

Joe Gemma  |  Advisory Board Member  |  Integrion Automation

Join Ron Müller, Seb Dignard, and Joe Gemma in this roundtable that will explore the evolving landscape of machine vision technology amid the rise of humanoid robots. As humanoids integrate advanced sensing, perception, and AI capabilities, these machine vision experts will examine whether traditional machine vision systems face obsolescence or will coexist synergistically. Moderated by Vision Systems Design's Head of Content Sharon Spielman, the panel will discuss challenges and opportunities in accuracy, adaptability, cost and application domains.

Key questions include:

• - Can humanoid vision surpass established systems in industrial and commercial sector?
• - Will the humanoids in mass-production be cheaper in purchase, integration, and operation?
• - How will the interplay between humanoid and traditional vision affect future automation,         safety, and human-robot collaboration?
•  

You don't want to miss this dynamic discussion on the future of machine vision.

Ronald Müller 

Sebastien Dignard

Joe Gemma