29 Result(s)
within
English
Computer Science
Robotics
Yi** **
Video Segment
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Video Segment
Voice Commands Using Arduino and Machine Learning
This segment provides a step by step guide on how to setup hardware components and use a tensorflowLite model to recognize ‘yes’ and ‘no’ voice commands.
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Build an Emoting Robot Using Arduino and Machine Learning
This video describes how to use Arduino and machine learning to create an emoting bot that recognizes different gestures.
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Challenges of Autonomous Driving systems
This video segment introduce the challenges for autonomous driving system.
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Mobile Robot Hardware
This video discusses the hardware components of mobile robots, including drive mechanics, controllers, sensors and the overall system design.
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Lane detection
In this video segment, we provide overall overview of existing Lane detection algorithm, including traditional and deep learning based solutions.
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Robot Simulation: Concept, Setup
This video segment explains the concept of robot simulation and gives an introduction to the EyeSim simulation system.
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Mazes: Exploration
This video segment introduces mazes and their simulation environment format. Iterative (left-hand rule) and recursive algorithms for maze exploration are shown.
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SLAM in Autonomous Driving
This video segment shows how we can create high definition map using the SLAM technology. And also we are using the Autoware AVP as one example to show how SLAM can be applied into the autonomous driving.
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Lidar: Light Detection and Ranging
This video introduces the concept of a Lidar sensor and its applications. A Lidar is used for a predator-prey simulation as well as for driving a real and a simulated Formula-SAE Autonomous race car.
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Autonomous Boats and Submarines (AUV)
This video part shows real and simulated autonomous underwater vehicles (AUV) and autonomous boats. Sample programs for basic movements patterns are shown.
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Robot Vision: Motion Detection
This video segment analyses image sequences, identifying changes that are due to motion in the image field. This concept is then extended to tracking moving objects.
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Outlook: Virtual Reality, Autonomous Vehicles, Projects
This video concludes the s0eries by giving an outlook at more ambitious robotics projects, including EyeSim Virtual Reality on the Oculus Quest. The video highlights more complex autonomous vehicles and introd...
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Deep Learning Model Optimization
In this video segment, we will mainly go through the algorithms for deep learning model optimization.
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Autonomous SoC development
This video segment mainly introduce one SoC development from TI and another SoC development from academic.
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Autonomous Driving Software Architecture
This video segment introduces how the safety features should be incorporated into the whole software design pipeline and introduces some tools from commercial companies to help the software design and show one...
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Introduction
This video gives a general introduction to robotics. It shows the robots we work on in the UW Robotics Lab and discusses different types of real and simulated robots.
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3D object detection
In this video segment, we will mainly go through the algorithms for 3D object detection and finally use one paper to show we can develop 3D object detection algorithm.
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Mobile Robot Software
This video gives an introduction into the software setup and connection between a robot and a laptop/desktop computer. It shows how to transfer files, do a remote login, compile and run application programs.
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Motion Planning and Control
This video segment mainly introduce three different approaches to address the motion planning and control for autonomous driving. For deep learning based solution, we use one L5Kit as one example showing how w...
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Robot Simulation: Examples
This video segment demonstrates the use of the EyeSim robot simulator by introducing several sample robot application programs.
