How do warehouse robots achieve 360-degree environmental awareness in busy, dynamic environments?

In this episode of Vision Vitals - e-con Systems podcast, we dive into how multi-camera systems give Autonomous Mobile Robots (AMRs) full spatial perception for safe navigation, obstacle detection, inventory inspection, docking accuracy, and more.

🎙️ In this episode, you’ll learn:
✅ Why a single camera isn’t enough for warehouse automation
✅ How front, rear, and side cameras eliminate blind spots
✅ The role of stereo depth and distance estimation
✅ How synchronized camera feeds reduce latency and misalignment
✅ Real-world use cases including shelf inspection, lane following, and collision avoidance
✅ How HDR sensors adapt to mixed warehouse lighting
✅ Hardware challenges (wiring, thermal, vibration) and how to solve them
✅ How interfaces like GMSL2 simplify multi-camera integration

🌐 Explore Multi-Camera Solutions for Warehouse Robots:

🔔 Subscribe to stay tuned for more conversations that put the future of vision in focus.

How do Autonomous Mobile Robots (AMRs) perceive the world around them?
In this episode of Vision Vitals - e-con Systems Podcast, we dive deep into how Time of Flight (ToF) technology enables AMRs to “see” in 3D — helping them navigate complex environments safely and intelligently.

🎙️ In this episode:

• What Time of Flight cameras are and how they work
• Why ToF depth sensing is critical for navigation and obstacle avoidance
• Key advantages over traditional stereo or RGB cameras
• Real-world use cases where e-con Systems’ DepthVista ToF cameras power warehouse and industrial robots

You’ll also hear about how ToF data integrates with NVIDIA Jetson platforms, supports SLAM, and enhances real-time safety through accurate 3D mapping.

Whether you’re a robotics developer, automation engineer, or AI enthusiast — this episode will change how you think about robotic vision.

🎧 Listen now and explore the depth of ToF technology in action.

#AutonomousMobileRobots #TimeofFlight #ToFCamera #VisionVitals #RoboticsVision #DepthSensing #econSystems #MachineVision #EmbeddedVision

n this episode of Vision Vitals by e-con Systems, we explore how camera technology shapes the navigation, perception, and safety of Autonomous Mobile Robots (AMRs).

From SLAM-based navigation to real-time obstacle detection, the right camera setup determines how intelligently and safely an AMR can operate.

Tune in to learn:

• Why AMRs depend on global shutter, HDR, and RGB-IR cameras
• How depth and stereo cameras enable 3D perception
• The importance of high-speed interfaces like GMSL2 for multi-camera systems
• How TintE ISP and Jetson Orin integration optimize imaging pipelines
• Real-world examples of AMR deployments in warehouses and industrial settings

📌 Explore e-con Systems’ AMR camera solutions

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🎙️ Welcome to Vision Vitals — your source for insights into the future of embedded vision.

In this episode, we break down TintE ISP, e-con Systems’ in-house Image Signal Processor (ISP) built on FPGAs — and explore how it revolutionizes image quality, flexibility, and system performance across industries like robotics, industrial automation, and medical imaging.

Learn how TintE:
✅ Processes raw Bayer data into clear, accurate images
✅ Handles noise reduction, HDR, tone mapping, and color correction
✅ Offloads image processing from CPU/GPU for faster AI and analytics
✅ Scales across platforms like Lattice, Xilinx, and Intel
✅ Powers consistent vision for Jetson Thor and edge AI applications

💡 Tune in to discover how TintE ISP enables superior image quality and real-time performance for modern vision systems.

🔔 Subscribe to stay tuned for more conversations that put the future of vision in focus.

In this episode of Vision Vitals – e-con Systems Podcast, we unpack the 10G Compact HSB Camera Solution that’s changing the game for NVIDIA Jetson Thor & Orin platforms.

✅ What you’ll learn:

• Why 10G Ethernet solves bandwidth and latency challenges
• How TintE ISP offloads GPU/CPU for faster AI inference
• Sensor options: 20MP AR2020 (super-resolution) & AR0234 (global shutter)
• Real-world use cases in robotics, medical imaging, industrial inspection & AI research
• Why compact HSB design matters for edge AI deployments

📌 Explore more about e-con's 10G Holoscan Cameras for NVIDIA Platforms

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In this episode of Vision Vitals, we explore how e-con Systems, a long-time NVIDIA Elite Partner, enables developers to fully leverage the power of Jetson AGX Thor.

What you’ll learn:
🔹 How e-con’s high-performance cameras are validated for Jetson Thor
🔹 The role of the TintE ISP in offloading GPU workloads
🔹 Why the ECU compute platform accelerates time-to-market
🔹 How the Vision Box helps bridge the gap between prototype and production

Whether you’re building for robotics, 3D perception, or autonomous machines, this episode explains how to speed up deployment with a complete vision ecosystem.

📌Explore our Jetson Thor solutions:

👉 Cameras for Jetson AGX Thor

👉 Vision Box for Jetson Thor

🔔 Subscribe to stay tuned for more conversations that put the future of vision in focus.

In this episode of Vision Vitals - e-con Systems podcast, we dive into one of the most anticipated comparisons in embedded AI: NVIDIA Jetson AGX Thor vs Jetson AGX Orin.

What does NVIDIA Jetson AGX Thor really bring to the table, and how does it change the game for developers already working with NVIDIA Jetson AGX Orin?

🎧 In this episode, you’ll learn:
🔹 The performance leap – FP4 TFLOPS vs Orin’s TOPS
🔹 How Thor improves memory, I/O, and multi-camera support
🔹 Real-world use cases in robotics, 3D perception, and autonomous machines
🔹 Migration strategies for developers moving from Jetson AGX Orin to Jetson AGX Thor
🔹 Why e-con Systems’ cameras are optimized for both platforms

Whether you’re building next-gen robots, industrial automation, or multi-camera AI systems, this discussion helps you decide when to stick with Orin — and when Thor unlocks new possibilities.

👉 Tune in now and explore the future of AI-powered embedded vision.

In this episode of Vision Vitals, we unpack NVIDIA Jetson AGX Thor, the system-on-module redefining robotics and embedded vision. With up to 2070 FP4 TFLOPS and 128 GB memory, Thor enables advanced workloads once thought impossible at the edge.

We look at how Thor compares with Jetson AGX Orin, what “Physical AI” means in practice, and how developers can leverage its compute density for multi-camera fusion, 3D perception, and predictive modeling. From humanoids and mobile robots to industrial and healthcare systems, we examine the role of this platform in the next era of AI-powered machines!

Stay subscribed for expert conversations on the future of embedded vision.