Acerca de este Curso
4.2
676 calificaciones
181 revisiones
Programa Especializado
100 % en línea

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.
Horas para completar

Aprox. 11 horas para completar

Sugerido: 3 hours/week...
Idiomas disponibles

Inglés (English)

Subtítulos: Inglés (English), Español (Spanish)

Habilidades que obtendrás

Motion PlanningAutomated Planning And SchedulingA* Search AlgorithmMatlab
Programa Especializado
100 % en línea

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.
Horas para completar

Aprox. 11 horas para completar

Sugerido: 3 hours/week...
Idiomas disponibles

Inglés (English)

Subtítulos: Inglés (English), Español (Spanish)

Programa - Qué aprenderás en este curso

Semana
1
Horas para completar
4 horas para completar

Introduction and Graph-based Plan Methods

Welcome to Week 1! In this module, we will introduce the problem of planning routes through grids where the robot can only take on discrete positions. We can model these situations as graphs where the nodes correspond to the grid locations and the edges to routes between adjacent grid cells. We present a few algorithms that can be used to plan paths between a start node and a goal node including the breadth first search or grassfire algorithm, Dijkstra’s algorithm and the A Star procedure....
Reading
5 videos (Total 27 minutos), 4 readings, 4 quizzes
Video5 videos
1.2: Grassfire Algorithm6m
1.3: Dijkstra's Algorithm4m
1.4: A* Algorithm6m
Getting Started with the Programming Assignments3m
Reading4 lecturas
Computational Motion Planning Honor Code10m
Getting Started with MATLAB10m
Resources for Computational Motion Planning10m
Graded MATLAB Assignments10m
Quiz1 ejercicio de práctica
Graph-based Planning Methods8m
Semana
2
Horas para completar
2 horas para completar

Configuration Space

Welcome to Week 2! In this module, we begin by introducing the concept of configuration space which is a mathematical tool that we use to think about the set of positions that our robot can attain. We then discuss the notion of configuration space obstacles which are regions in configuration space that the robot cannot take on because of obstacles or other impediments. This formulation allows us to think about path planning problems in terms of constructing trajectories for a point through configuration space. We also describe a few approaches that can be used to discretize the continuous configuration space into graphs so that we can apply graph-based tools to solve our motion planning problems....
Reading
6 videos (Total 19 minutos), 3 quizzes
Video6 videos
2.2: RR arm2m
2.3: Piano Mover’s Problem3m
2.4: Visibility Graph3m
2.5: Trapezoidal Decomposition1m
2.6: Collision Detection and Freespace Sampling Methods4m
Quiz1 ejercicio de práctica
Configuration Space8m
Semana
3
Horas para completar
1 hora para completar

Sampling-based Planning Methods

Welcome to Week 3! In this module, we introduce the concept of sample-based path planning techniques. These involve sampling points randomly in the configuration space and then forging collision free edges between neighboring sample points to form a graph that captures the structure of the robots configuration space. We will talk about Probabilistic Road Maps and Randomly Exploring Rapid Trees (RRTs) and their application to motion planning problems....
Reading
3 videos (Total 17 minutos), 2 quizzes
Video3 videos
3.2: Issues with Probabilistic Road Maps4m
3.3: Introduction to Rapidly Exploring Random Trees6m
Quiz1 ejercicio de práctica
Sampling-based Methods6m
Semana
4
Horas para completar
1 hora para completar

Artificial Potential Field Methods

Welcome to Week 4, the last week of the course! Another approach to motion planning involves constructing artificial potential fields which are designed to attract the robot to the desired goal configuration and repel it from configuration space obstacles. The robot’s motion can then be guided by considering the gradient of this potential function. In this module we will illustrate these techniques in the context of a simple two dimensional configuration space....
Reading
4 videos (Total 19 minutos), 2 quizzes
Video4 videos
4.2: Issues with Local Minima2m
4.3: Generalizing Potential Fields2m
4.4: Course Summary6m
Quiz1 ejercicio de práctica
Artificial Potential Fields6m
4.2
181 revisionesChevron Right
Beneficio de la carrera

50%

consiguió un beneficio tangible en su carrera profesional gracias a este curso

Principales revisiones

por FCNov 28th 2018

The course was challenging, but fulfilling. Thank you Coursera and University of Pennsylvania for giving this wonderful experience and opportunity that I might not experience in our local community!

por ADJul 3rd 2018

The topic was very interesting, and the assignments weren't overly complicated. Overall, the lesson was fun and informative , despite the bugs in the learning tool(especially, the last assignment.)

Instructor

Avatar

CJ Taylor

Professor of Computer and Information Science
School of Engineering and Applied Science

Acerca de University of Pennsylvania

The University of Pennsylvania (commonly referred to as Penn) is a private university, located in Philadelphia, Pennsylvania, United States. A member of the Ivy League, Penn is the fourth-oldest institution of higher education in the United States, and considers itself to be the first university in the United States with both undergraduate and graduate studies. ...

Acerca del programa especializado Robotics

The Introduction to Robotics Specialization introduces you to the concepts of robot flight and movement, how robots perceive their environment, and how they adjust their movements to avoid obstacles, navigate difficult terrains and accomplish complex tasks such as construction and disaster recovery. You will be exposed to real world examples of how robots have been applied in disaster situations, how they have made advances in human health care and what their future capabilities will be. The courses build towards a capstone in which you will learn how to program a robot to perform a variety of movements such as flying and grasping objects....
Robotics

Preguntas Frecuentes

  • Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.

  • Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.

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