Robotic Perception and Sensing

Major Related too : Robotics Engineering, Electrical Engineering, Computer Engineering, Mechanical Engineering, Automation, Computer Science

Description : "Robotic Perception and Sensing" explores the vital techniques enabling robots to understand and interact with their environment. Through the integration of advanced sensory technologies such as vision systems, lidar, and sensor fusion, robots gain the ability to perceive and interpret their surroundings. This minicourse delves into the fundamentals of computer vision, lidar technology, and sensor fusion methodologies, equipping learners with the knowledge to develop robust perception systems for robots. From object recognition to scene understanding, participants will explore cutting-edge approaches in machine learning and sensor calibration to enhance a robot's perception capabilities. By mastering these techniques, learners will unlock the potential for robots to navigate autonomously, interact intelligently with objects, and operate effectively in complex real-world environments.

• Robotic Perception and Sensing
  • Field Robotics: perception, machine learning and algorithms with Chris Heckman
  • Lecture 33 : LiDAR Technique and applications
  • Stanford Seminar - Robotic Autonomy and Perception in Challenging Environments
  • Sensor Fusion for Learning-based Motion Estimation in VR
  • Sensor Fusion in Self Driving Cars by Mohamed Ahmed
  • Environmental Modeling and Statistical Analysis
  • Lecture 11 – Semantic Parsing | Stanford CS224U: Natural Language Understanding | Spring 2019
  • Lecture 11: Simultaneous Localization and Mapping (SLAM)