Robotics Software Engineer Nanodegree

Robotics Software Engineer Nanodegree

English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 19h 50m | 4.92 GB

Master advanced robotics software engineering skills, and gain hands-on experience developing solutions that solve challenging robotics and AI problems.

In this program, you’ll gain hands-on experience developing robotics solutions as you cover topics such as: Robot Operating System (ROS), Kinematics, Control, Simultaneous Localization and Mapping (SLAM), and more. You’ll learn cutting-edge techniques like Deep Reinforcement Learning through our partnership with NVIDIA’s Deep Learning Institute. You’ll master the key skills necessary to become a software engineer in the transformational field of robotics and applied artificial intelligence.

Part 01 : Term 1: ROS Essentials, Perception, and Control
In this module, you’ll get an introduction to your Nanodegree program and obtain a comprehensive overview of the field that is Robotics. You’ll also build your first project, modeled after the NASA Mars Rover Challenge.

Part 02 : Term 2: Localization, Mapping, and Navigation
Learn to apply SLAM and reinforcement learning techniques for solving robotics problems.

Part 03 (Elective): Optional Kuka Path Planning Project
Solve a maze with path-planning and run it in simulation and hardware on a Kuka arm in the Kuka Challenge!

Table of Contents

1 Welcome
2 What is a Robot
3 Search and Sample Return
4 Career Support Overview
5 Introduction to ROS
6 Packages & Catkin Workspaces
7 Write ROS Nodes
8 GitHub
9 Udacity Explores – Biologically Inspired Robots
10 6 Questions on Robotics Careers
11 Intro to Kinematics
12 Forward and Inverse Kinematics
13 Project Robotic Arm Pick & Place
14 Udacity Explores – Human Robot Interaction & Robot Ethics
15 Product Pitch
16 Perception Overview
17 Introduction to 3D Perception
18 Calibration, Filtering, and Segmentation
19 Clustering for Segmentation
20 Object Recognition
21 3D Perception Project
22 Udacity Explores – Soft Robotics
23 Udacity Explores – Robot Grasping
24 Introduction to Controls
25 Quadrotor Control using PID
26 Udacity Explores Swarm Robotics
27 Networking in Robotics
28 Intro to Neural Networks
29 TensorFlow for Deep Learning
30 Deep Neural Networks
31 Convolutional Neural Networks
32 Fully Convolutional Networks
33 Lab Semantic Segmentation
34 Project Follow Me
35 Term 1 Outro
36 Introduction to C++ for Robotics
37 Introduction to Term 2
38 The Jetson TX2
39 Interacting with Robotics Hardware
40 Lab Hardware Hello World
41 Robotics Sensor Options
42 Inference Development
43 Inference Applications in Robotics
44 Project Robotic Inference
45 Introduction to Localization
46 Kalman Filters
47 Lab Kalman Filters
48 Monte Carlo Localization
49 Build MCL in C++
50 Project Where Am I
51 Introduction to Mapping and SLAM
52 Occupancy Grid Mapping
53 Grid-based FastSLAM
54 GraphSLAM
55 Project Map My World Robot
56 Intro to RL for Robotics
57 RL Basics
58 Q-Learning Lab
59 Deep RL
60 DQN Lab
61 Deep RL Manipulator
62 Project Deep RL Arm Manipulation
63 Intro to Path Planning and Navigation
64 Classic Path Planning
65 Lab Path Planning
66 Sample-Based and Probabilistic Path Planning
67 Research in Navigation
68 Project Home Service Robot
69 Strengthen Your Online Presence Using LinkedIn
70 Optimize Your GitHub Profile
71 Completing the Program
72 Project Introduction
73 Introduction to ROS
74 Packages & Catkin Workspaces
75 Write ROS Nodes
76 Search
77 Project Details