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Algorithmic Robotics and Motion Planning

Multi Robot Multi Robot Configuration Space
willowRobot

Spring 2018

0368-4010-01

Course hours: Monday, 16:00-19:00
Location: TBA

Instructor: Dan Halperin, danha AT post tau ac il
Office hours by appointment

Teaching assistant: Kiril Solovey, kirilsol at post tau ac il

 


The recent years have seen an outburst of new robotic applications and robot designs in medicine, entertainment, security and manufacturing to mention just a few areas. Novel applications require ever more sophisticated algorithms. In the course, we shall cover computational and algorithmic aspects of robotics with an emphasis on motion planning.

The motion-planning problem is a key problem in robotics. The goal is to plan a valid motion path for a robot (or any other mobile object for that matter) within a given environment, while avoiding collision with obstacles. The scope of the motion-planning problem is not restricted to robotics, and it arises naturally in different and diverse domains, including molecular biology, computer graphics, computer-aided design and industrial automation. Moreover, techniques that were originally developed to solve motion-planning problems have often found manifold applications.

The topics that will be covered include (as time permits):
 A brief tour of algorithmic problems in robotics
 The configuration space approach and the connection between motion planning and geometric arrangements
 Minkowski sums; exact and efficient solution to translational motion planning in the plane
 Translation and rotation in the plane; translational motion of polyhedra in space
  Sampling-based motion planning

  Collision detection

 Path quality: shortest paths, high clearance paths, and other quality measures
 Direct and inverse kinematics: from industrial manipulators to proteins
 Dynamic maintenance of large kinematics structures
  Multi-robot motion planning


Prerequisites 

Computational Geometry and knowledge of C++ or willingness to learn the language.

The course is geared towards graduate students in computer science. Third-year undergrads are welcome.

 

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