Robot Perception & Computer Vision
Enable robots to see and interpret their environment using cameras and other sensors. Study image processing, object detection, feature extraction, and 3D reconstruction techniques.
22 courses
Learn to build automated image processing and feature detection systems using LabVIEW, starting from foundational concepts to practical vision application design.
Discover how to leverage AWS to build, deploy, and manage intelligent cloud-connected robotics applications and fleet workloads.
Learn how to recover 3D structures from multiple 2D images using camera calibration, stereo geometry, and modern Python computer vision libraries.
Learn the principles of recovering 3D spatial information and scene structure from 2D images captured from a stationary camera.
Master the fundamentals of robotic design, programming, and vision systems to build intelligent automated solutions for modern industrial environments.
Learn to interpret orthorectified aerial imagery and use spatial data to communicate planning ideas and analyze urban landscapes effectively.
Master the core principles, design patterns, and modern development workflows needed to transition from writing simple scripts to building production-ready software.
Learn to analyze and solve complex relative velocity problems using a systematic vector approach designed for physics students and engineering exam aspirants.
Learn how modern digital cameras combine optics, sensors, and software algorithms to capture, process, and reconstruct rich visual data.
Master the essentials of 3D point cloud data, learn how to process spatial representations, and write your first 3D machine learning pipelines using PyTorch3D.
Learn the fundamentals of 3D registration to align spatial datasets using rotation, translation, and modern PyTorch3D implementations.
Learn to calibrate laser-based vision systems and reconstruct 3D surface topography for industrial inspection using modern computer vision concepts.
Learn the calibration techniques and mathematical foundations to reconstruct accurate 3D topography using cameras and structured light.
Learn the fundamentals of laser-based 3D scanning and surface reconstruction for automated industrial quality control.
Learn how to align images using OpenCV, perspective warping, and homography estimation to build precise automated quality control and inspection systems.
Master the Perspective-n-Point algorithm to determine camera position and orientation using 3D-to-2D point correspondences.
Learn the fundamentals of SAR imaging, interferometry, and polarimetry to analyze Earth observation data for environmental monitoring and disaster management.
Learn to calculate homography matrices and warp skewed images for computer vision alignment and inspection tasks.
Learn the foundational concepts of computer vision and machine learning to build robots that can navigate safely, avoid obstacles, and interact with their environments.
Learn the mathematical foundations of robotic movement, coordinate systems, and kinematics to build a strong basis for modern robotics engineering.
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