Vectornav VN-200 Manual de usuario

Autonomous Navigation and Collision AvoidanceRobotPengqi ChengElectrical Engineering and Computer SciencesUniversity of California at BerkeleyTechnica

For example, Stanford’s Junior uses two quad core computers as a cluster to support all thecomputation. As the performance of computers has evolved a

4 Methodology4.1 GPS ChoicesIn a navigation system, a GPS sensor is required to get location information. In the originaldesign, the ideal way is to u

what development kit do we use? In order to make the development easier, we want the kit toprovide convenient development environment s o that we only

4.2 GPS Driver ImplementationAfter making decision, we found that we still finally need to use the sensor on the Orca system,although the driver native

2. State c ontrol methods : enable, disable, init, shutdown, resetVN200 will automatically send data in a specified frequency after configuration. The d

5 Discussion5.1 GPS DriverThis section will firs t show th e results of the GPS dri ver and make some comparison and expla-nation.Before making any cha

Therefore, th er e is just one more step left – integrate this VN200 driver into the Orca system.With these steps before, what we need to do is just w

random data for testing. Thus, it makes me hard to compare this driver with other mature platforms.The only other actual driver that we can compare wi

Figure 6 Screenshot of Motor Encoder Driver5.3 EvaluationIt is hard to give out a quantitative evaluation of this project, s inc e the work is mostly

a better communication and real-time controlling, embedded subsystems like Orca are designed.Usually, hardware vendors might not write a specific inter

Copyright © 2013, by the author(s).All rights reserved. Permission to make digital or hard copies of all or part of this work forpersonal or classroom

6 ConclusionI learned quite a lot from this capstone project. In the technical part, I learned how to developdrivers and applications in an embedded s

References[1] Plunkett Research. 2012. Automobiles and Truck Trends.http://www.plunkettresearch.com/automobiles -tr u cks-market-research/industry-tre

[13] F. Dellaert, W. Burgard, D. Fox and S. Thrun. 1999. Using the CONDENSATION Algorithm forRobust, Vision-based Mobile Robot Localization. Proceedin

[25] R. Sukthankar. 1992. Raccoon: A Real-Time Autonomous Car Chaser Operating Optimally atNight. CMU-RI-TR-92-13, Carnegie-Mellon University Pittsbur

Masters Project PaperAutonomous Navigation and CollisionAvoidance RobotPengqi ChengElectrical Engineering and Computer SciencesUniversity of Californi

1 AbstractIn the last 50 years, information technology has automated many jobs like word proc es s in g,mathematical calculation and data retrieval. H

2 IntroductionThe number of motor vehicles has reached more than one billion one billion in the world, whichhas expande d for nearly ten times since t

• No need of redundant passengers for driving [11] since the car can move without human driver.• Less jobs needed such as driver, traffic police and tol

3 Literature ReviewAutonomous driving is not an easy task. It involves various su bjects and technologies such asautomation control [12], computer vis

The Google driverless car (Figure 1) is n ot just one car or one type of car. Instead, it is a projectinvolving at least eight vehicles consisting of

3.3 Nissan’s Mixed-mode DesignsUnlike the two automated system, Nissan leverages many technologies to make driving safer andmore comfortable. An examp