Robo-Magellan Project (SRS Robothon Competition entry)

Robo-Magellan Project

 

 

 

 

 

 

 

 

 

 

****Jigsaw is building a self navigating robot to compete at the Robothon on June 2, and we need more team members and mentors. would you help please.*****


PS: Professor Sebastian Thrun will help us complete programming all the major systems of a robotic car over the course of seven weeks. (CS373 - PROGRAMMING A ROBOTIC CAR)

 

Lead: Shubham Shukla

Host: Budi Mulyo

(Jigsaw Renaissance)

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More info:SRS Robo-Magellan - http://www.robothon.org/robothon/robo-magellan.php-------------------------------------------------------------http://www.jigsawrenaissance.org/2012/03/robo-magellan-project-srs-robotics-competition-entr...

What we are given
  • latitude and longitude of start point, destination, waypoints
    • accurate to 4 decimal places
    • might be places where GPS might not work (fall back to SLAM)
  • Course:
    • Start -> Waypoint 1 -> Waypoint 2 -> Waypoint 3 -> destination
  • Challenges:
    • Obstacle avoidance
    • Cone detection (2 phase process)
    • Surviving with weak lost GPS signals
    • Be able to travel over a variety of diverse terrain such as grass, sand and concrete
    • Optional/mandatory waypoints
Interesting points from the Rule book
  • They use “datum WGS84″ for GPS from Google Earth.
  • Recording latitudes and longitudes that are accurate with respect to each other is more important than recording latitudes and longitudes that are accurate with respect to surveyed points. In other words, it’s more important a builder knows the distance and bearing between points than it is for them to accurately navigate to a surveyed location.
Interesting Videos High Level Algorithm
  • Follow the path from start point to each way-point and finally to destination using GPS and SLAM
  • Implement obstacle avoidance and control
  • Image processing: detect triangle shaped orange color when the robot is within x distance from the waypoint
  • Some way to check that the robot ‘touched’ the waypoint (touch sensors?)
Real World Application

Sebastian Thrun helped build Google’s amazing driverless car, powered by a very personal quest to save lives and reduce traffic accidents. Jawdropping video shows the DARPA Challenge-winning car motoring through busy city traffic with no one behind the wheel, and dramatic test drive footage from TED2011 demonstrates how fast the thing can really go.

In 2005, Stanley won $2,000,000 prize by winning the DARPA Grand Challenge, the largest prize money in robotic history. Stanley is an autonomous vehicle created by Stanford University’s Stanford Racing Team. The leader of Google and Stanford’s autonomous driving teams who created Stanley, Professor Sebastian Thrun is showing us how to program all the major systems of a robotic car at the Udacity, the free online course. Check out TED Talk – Sebastian Thrun: Google’s driverless car.

 

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