MM-UAV: Mobile Manipulating Unmanned Aerial Vehicle

Abstract

Given significant mobility advantages, UAVs have access to many locations that would be impossible for an unmanned ground vehicle to reach, but UAV research has historically focused on avoiding interactions with the environment. Recent advances in UAV size to payload and manipulator weight to payload ratios suggest the possibility of integration in the near future, opening the door to UAVs that can interact with their environment by manipulating objects. Therefore, we seek to investigate and develop the tools that will be necessary to perform manipulation tasks when this becomes a reality. We present our progress and results toward a design and physical system to emulate mobile manipulation by an unmanned aerial vehicle with dexterous arms and end effectors. To emulate the UAV, we utilize a six degree-of-freedom miniature gantry crane that provides the complete range of motion of a rotorcraft as well as ground truth information without the risk associated with free flight. Two four degree-of-freedom manipulators attached to the gantry system perform grasping tasks. Computer vision techniques and force feedback servoing provide target object and manipulator position feedback to the control hardware. To test and simulate our system, we leverage the OpenRAVE virtual environment and ROS software architecture. Because rotorcraft are inherently unstable, introduce ground effects, and experience changing flight dynamics under external loads, we seek to address the difficult task of maintaining a stable UAV platform while interacting with objects using multiple, dexterous arms. As a first step toward that goal, this paper describes the design of a system to emulate a flying, dexterous mobile manipulator.

This is a preview of subscription content, access via your institution.

References

  1. 1.

    http://www.hdtglobal.com/services/robotics/MK1-robotic-arm/

  2. 2.

    http://dasl.mem.drexel.edu/pire/

  3. 3.

    Pines, D., Bohorquez, F.: Challenges facing future micro air vehicle development. AIAA J. Aircraft 43(2), 290–305 (2006)

    Article  Google Scholar 

  4. 4.

    Hein, B., Chopra, I.: Hover performance of a micro air vehicle: rotor at low Reynolds number. J. Am. Helicopter Soc. 52(3), 254–262 (2007)

    Article  Google Scholar 

  5. 5.

    Michael, N., Mellinger, D., Lindsey, Q., Kumar, V.: The GRASP multiple micro UAV testbed. In: IEEE Robotics and Automation Magazine (2010)

  6. 6.

    Hoffmann, G. Rajnarayan, D., Waslander, S. Dostal, D. Jang, J., Tomlin, C.: The stanford testbed of autonomous rotorcraft for multi-agent control. In: Digital Avionics System Conference 2004, Salt Lake City, UT (2004)

  7. 7.

    Pounds, P., Dollar, A.: Hovering stability of helicopters with elastic constraints. In: Proceedings of the 2010 ASME Dynamic Systems and Control Conference (2010)

  8. 8.

    Mellinger, D., Shomin, M., Michael, N., Kumar, V.: Cooperative grasping and transport using multiple quadrotors. In: Distributed Autonomous Robotic Systems. Lausanne, Switzerland (2010)

    Google Scholar 

  9. 9.

    Kuntz, N., Oh, P.Y.: Towards autonomous cargo deployment and retrieval by an unmanned aerial vehicle using visual servoing. In: ASME Dynamic Systems and Controls Conference (2008)

  10. 10.

    Narli, V., Oh, P.Y.: Hardware-in-the-loop test rig to capture aerial robot and sensor suite performance metrics. In: IEEE International Conference on Intelligent Robots and Systems, p. 2006. Beijing, China (2006)

    Google Scholar 

  11. 11.

    Ng, A.Y., Kim, H., Jordan, M. Sastry, S.: Autonomous helicopter flight via reinforcement learning. In: Advances in Neural Information Processing Systems. MIT Press (2004)

  12. 12.

    Hing, J., Sevcik, K., Oh, P.Y.: Improving unmanned aerial vehicle pilot training and operation for flying in cluttered environments. In: International Conference on Intelligent Robots and Systems, pp. 5641–5646. St. Louis, MO, 10–15 October 2009

  13. 13.

    http://www.robotis.com/xe/dynamixel_en

  14. 14.

    Quigley, M., Conley, K., Gerkey, B., Faust, J., Foote, T.B. Leibs, J., Wheeler, R., Ng, A.Y.: Ros: an open-source robot operating system. In: ICRA, Ser. Open-Source Software Workshop. IEEE (2009)

  15. 15.

    Diankov, R., Kuffner, J.: Openrave: a planning architecture for autonomous robotics. Tech. Rep. CMU-RI-TR-08-34, Robotics Institute, Carnegie Mellon University (2008)

  16. 16.

    Hamner, B., Koterba, S., Shi, J., Simmons, R., Singh, S.: An autonomous mobile manipulator for assembly tasks. Auton. Robots 28, 131–149 (2010)

    Article  Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Christopher M. Korpela.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Korpela, C.M., Danko, T.W. & Oh, P.Y. MM-UAV: Mobile Manipulating Unmanned Aerial Vehicle. J Intell Robot Syst 65, 93–101 (2012). https://doi.org/10.1007/s10846-011-9591-3

Download citation

Keywords

  • Mobile manipulation
  • Unmanned aerial vehicle
  • Dexterous arms