In response to an abundance of applications, Unmanned Aerial Vehicles are being called upon to perform missions of high difficulty for increasingly long periods of time. Traditional paradigms of propeller design and actuation are reaching a design ceiling, motivating creative approaches to the design of propeller-based propulsion mechanisms. Within the last decade, one particular kind of mechanism, the variable-pitch propeller, has been studied by researchers for its applications to the class of small UAVs. This paper pushes for new results in this area by exploring the use of Variable Pitch Propulsion (VPP) to minimize power consumption for small, versatile UAVs. A control algorithm is presented to minimize the consumed electrical power during a quasi-steady propulsive state. In particular, the algorithm is not confined to operation in limited regions of the state space, but it seeks to minimize power at whatever point in the state space a steady state is reached. Several experimental results are presented to validate the approach.
|Original language||English (US)|
|Title of host publication||2019 International Conference on Robotics and Automation, ICRA 2019|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||6|
|State||Published - May 2019|
|Event||2019 International Conference on Robotics and Automation, ICRA 2019 - Montreal, Canada|
Duration: May 20 2019 → May 24 2019
|Name||Proceedings - IEEE International Conference on Robotics and Automation|
|Conference||2019 International Conference on Robotics and Automation, ICRA 2019|
|Period||5/20/19 → 5/24/19|
Bibliographical noteFunding Information:
The authors would like to thank all the members of the Center for Distributed Robotics Laboratory for their help. In addition, the authors gratefully acknowledge James Williams
The authors would like to thank all the members of the Center for Distributed Robotics Laboratory for their help. In addition, the authors gratefully acknowledge James Williams for piloting the aerial testbed during data collection. This material is based upon work partially supported by the National Science Foundation through grants IIS-1427014, CNS-1439728, CNS-1531330, and CNS-1544887. Sentera Inc. and Honeywell Inc. have also supported parts of this work.
© 2019 IEEE.