Acerca de este Curso

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Fechas límite flexibles
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Nivel avanzado
Aprox. 32 horas para completar
Inglés (English)
Subtítulos: Inglés (English)
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel avanzado
Aprox. 32 horas para completar
Inglés (English)
Subtítulos: Inglés (English)

ofrecido por

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Universidad de Toronto

Programa - Qué aprenderás en este curso

Semana
1

Semana 1

1 hora para completar

Welcome to Course 4: Motion Planning for Self-Driving Cars

1 hora para completar
4 videos (Total 18 minutos), 3 lecturas
4 videos
Welcome to the Course3m
Meet the Instructor, Steven Waslander5m
Meet the Instructor, Jonathan Kelly2m
3 lecturas
Course Readings10m
How to Use Discussion Forums15m
How to Use Supplementary Readings in This Course15m
2 horas para completar

Module 1: The Planning Problem

2 horas para completar
4 videos (Total 54 minutos), 1 lectura, 1 cuestionario
4 videos
Lesson 2: Motion Planning Constraints13m
Lesson 3: Objective Functions for Autonomous Driving9m
Lesson 4: Hierarchical Motion Planning17m
1 lectura
Module 1 Supplementary Reading10m
1 ejercicio de práctica
Module 1 Graded Quiz50m
Semana
2

Semana 2

6 horas para completar

Module 2: Mapping for Planning

6 horas para completar
5 videos (Total 50 minutos), 1 lectura, 1 cuestionario
5 videos
Lesson 2: Populating Occupancy Grids from LIDAR Scan Data (Part 1)9m
Lesson 2: Populating Occupancy Grids from LIDAR Scan Data (Part 2)9m
Lesson 3: Occupancy Grid Updates for Self-Driving Cars9m
Lesson 4: High Definition Road Maps11m
1 lectura
Module 2 Supplementary Reading1h
Semana
3

Semana 3

4 horas para completar

Module 3: Mission Planning in Driving Environments

4 horas para completar
3 videos (Total 35 minutos), 1 lectura, 1 cuestionario
3 videos
Lesson 2: Dijkstra's Shortest Path Search10m
Lesson 3: A* Shortest Path Search13m
1 lectura
Module 3 Supplementary Reading1h
1 ejercicio de práctica
Module 3 Graded Quiz50m
Semana
4

Semana 4

2 horas para completar

Module 4: Dynamic Object Interactions

2 horas para completar
3 videos (Total 36 minutos), 1 lectura, 1 cuestionario
3 videos
Lesson 2: Map-Aware Motion Prediction11m
Lesson 3: Time to Collision12m
1 lectura
Module 4 Supplementary Reading1h
1 ejercicio de práctica
Module 4 Graded Quiz50m

Reseñas

Principales reseñas sobre MOTION PLANNING FOR SELF-DRIVING CARS

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Acerca de Programa especializado: Automóviles de auto conducción

Be at the forefront of the autonomous driving industry. With market researchers predicting a $42-billion market and more than 20 million self-driving cars on the road by 2025, the next big job boom is right around the corner. This Specialization gives you a comprehensive understanding of state-of-the-art engineering practices used in the self-driving car industry. You'll get to interact with real data sets from an autonomous vehicle (AV)―all through hands-on projects using the open source simulator CARLA. Throughout your courses, you’ll hear from industry experts who work at companies like Oxbotica and Zoox as they share insights about autonomous technology and how that is powering job growth within the field. You’ll learn from a highly realistic driving environment that features 3D pedestrian modelling and environmental conditions. When you complete the Specialization successfully, you’ll be able to build your own self-driving software stack and be ready to apply for jobs in the autonomous vehicle industry. It is recommended that you have some background in linear algebra, probability, statistics, calculus, physics, control theory, and Python programming. You will need these specifications in order to effectively run the CARLA simulator: Windows 7 64-bit (or later) or Ubuntu 16.04 (or later), Quad-core Intel or AMD processor (2.5 GHz or faster), NVIDIA GeForce 470 GTX or AMD Radeon 6870 HD series card or higher, 8 GB RAM, and OpenGL 3 or greater (for Linux computers)....
Automóviles de auto conducción

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