Technology Deep Dive Archives - Page 2 of 17

How to Overcome Vision Challenges While Building a Multi-Robot Mapping System (Part 2)

Arun AsokanApril 15, 20260

Arun AsokanArun is a seasoned Embedded Vision leader with 11+ years of experience driving innovation in robotics and AI-powered imaging systems. He focuses on developing perception stacks that power intelligent robotic systems, bridging hardware, algorithms, and edge deployment.

What Are the 5 Key Features of 3D iToF Cameras – And How Does DepthVista Helix Offer Them?

Prabu KumarFeb 20, 20260

In an era where spatial awareness and depth perception are becoming crucial, 3D imaging technology has become more popular than ever. This has resulted in Time-of-Flight (iToF) cameras, an advanced imaging solution, changing how machines perceive and interact with the world around them. Unlike traditional 2D cameras that capture only...

Why Multi-Robot Autonomous Mapping Is Becoming Essential for Large-Scale Facilities (Part 1)

Arun AsokanApril 15, 20260

Arun AsokanArun is a seasoned Embedded Vision leader with 11+ years of experience driving innovation in robotics and AI-powered imaging systems. He focuses on developing perception stacks that power intelligent robotic systems, bridging hardware, algorithms, and edge deployment.

Lattice FPGA–Based Holoscan Cameras on NVIDIA AGX Thor & Orin for Scalable Multi-Sensor Edge AI Systems

Prabu KumarMarch 24, 20260

Present-day edge AI systems rely heavily on multi-modal sensor fusion, such as camera, LiDAR, and Radar, to enable accurate, real-time decision-making. Existing platforms, such as NVIDIA Jetson Orin NX, are equipped to adequately support multi-camera use cases. To advance this further, NVIDIA’s latest Jetson Thor series modules have been combined

A Detailed Guide to Confidence Filtering in Indirect Time of Flight Cameras

Prabu KumarFebruary 17, 20260

Indirect Time-of-Flight (iToF) sensors are among the most widely used 3D camera technologies for depth estimation. However, noisy depth measurements can limit their ability to deliver reliable, high-quality depth data. Applying appropriate filtering techniques helps improve accuracy by suppressing noisy pixels and enhancing depth reliability.

Clear HDR vs DOL HDR: Which HDR Technology is Right for Your Application?

Prabu KumarFebruary 19, 20260

Embedded vision applications require the camera image sensor to capture a clear image under challenging illumination conditions, with no motion artifacts. The Sony STARVIS 2 image sensor family will meet this requirement by supporting advanced HDR modes, including clear HDR and DOL HDR, enabling high-end embedded vision cameras to deliver

3D Mobile Mapping for Digital Twins: Camera Features That Ensure Accuracy

Ram PrasadJanuary 28, 20260

Digital twins depend on how accurately physical environments are captured, reconstructed, and updated over time. Mobile mapping systems feed imaging data of streets, facilities, and structures into photogrammetry and SLAM pipelines to create virtual models. Therefore, camera performance determines if a digital twin can support simulation, planning, and monitoring with

Sony Pregius IMX264 vs. IMX568: A Detailed Sensor Comparison Guide

Prabu KumarJanuary 13, 20260

IMX264 and IMX568 both belong to the Sony Pregius family of image sensors, which feature global-shutter pixels. Both sensors are renowned for their sensitivity, low noise, and distortion-free imaging, and are well-suited to high-speed vision applications, especially those requiring light sensitivity. While both sensors belong to the same Pregius family,

What is a dust denoising filter in TOF camera, and how does it remove noise artifacts in vision systems?

Prabu KumarMarch 3, 20260

Time-of-Flight (ToF) cameras with IR sensors are susceptible to performance variations caused by environmental dust. This dust can create 'dust noise' in the output depth map, directly impacting camera accuracy and, consequently, the reliability of critical embedded vision applications.

Indirect Time-of-Flight: Continuous-Wave or Pulsed – Which Suits Your Needs?

Prabu KumarDecember 5, 20250

Indirect ToF has emerged as a practical depth-sensing method for automation, robotics, and mobility systems. CW and pulsed approaches achieve depth measurement differently, shaping their performance in controlled or outdoor conditions. CW systems leverage phase shifts for fine mapping and richer scene data, while pulsed systems rely on timing offsets