UPenn

q  

 estimate position within several mm, and updates at 200Hz

 Vicon Motion Capture system, please click on this link.

 https://www.coursera.org/learn/robotics-flight/lecture/ZL921/supplementary-material-lab-introduction

 

 calibration

                                 

  

 these are indoor estimation, but how about out door situations?

 

 

 

 

 imu for the position transformation?

laser  or camera for angle and distance measurement?

 

 

This is SLAM!!!!

 

 To learn more about how we use the Multi-Sensor Unscented Kalman Filter, and how we build 3-D maps, please see sections 5.2 and 3.3 of the following thesis:

 https://d18ky98rnyall9.cloudfront.net/_442e88b97aa6aea46ee426a54c797700_shaojie_shen_thesis.pdf?Expires=1539648000&Signature=PxHn2SPu2b5W-y3qmWG330Op81sw-VjjEEZA~a2poV6WxBDq4WwhZILzCWMpCdr9UAHvFChhnMVW7foh~uUcubNow24RlshyzzwVheM4L-0yqVYo1-0knZevnqU0yYku1jzcEWQahuDfsjD8QiCJ-Dvzx0cMAA2Vfu2PCzVJFR8_&Key-Pair-Id=APKAJLTNE6QMUY6HBC5A

 

 

 

 

 

 

 

 

 

But as you see from these pictures, as the vehicle manuevers at high speeds and exhibits roll and pitch angles far away from zero, these kinds of controllers are not likely to work.

 

 

 

 

 

 

 

 

 

 

https://www.youtube.com/watch?v=mZhwK_y3a2Y

 inertia is small

 

 

 

 To learn more about how we use the nonlinear controller and how we plan three dimensional trajectories, please see the relevant chapters in the thesis below.

 https://d18ky98rnyall9.cloudfront.net/_7f3305d57403df299005db44f23852a3_daniel_mellinger_thesis.pdf?Expires=1539648000&Signature=QyzmO7g0WIOVCxSe2sOVb5hW5x37drrLFTKtl~F8jSVCPQbXKrT2a~dOfcpY4NKYsNcsYKAiZA~LpE048YRhn~joPmrw4y1kGT8FtHzIAJIOAjjQNm7vdlkvCsgX-Vq-GirecX~4PQgErQuDNpZ2i-HHldWVWAys59ofFZoZMko_&Key-Pair-Id=APKAJLTNE6QMUY6HBC5A

 

 

 

 

 

 

 

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3D printing????? by drones???

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  

    

 considering   payloads

 

 

 

 

 

 

 

 

 

 

 

 To learn more about collaborative mapping between aerial and ground robots, please refer to the doctoral thesis by Benjamin Charrow, Information-theoretic active perception for multi-robot teams: