@article{(Open Science Index):https://publications.waset.org/pdf/10003479,
	  title     = {Super-ellipsoidal Potential Function for Autonomous Collision Avoidance of a Teleoperated UAV},
	  author    = {Mohammed Qasim and  Kyoung-Dae Kim},
	  country	= {},
	  institution	= {},
	  abstract     = {In this paper, we present the design of the
super-ellipsoidal potential function (SEPF), that can be used for
autonomous collision avoidance of an unmanned aerial vehicle (UAV)
in a 3-dimensional space. In the design of SEPF, we have the
full control over the shape and size of the potential function. In
particular, we can adjust the length, width, height, and the amount
of flattening at the tips of the potential function so that the collision
avoidance motion vector generated from the potential function can
be adjusted accordingly. Based on the idea of the SEPF, we also
propose an approach for the local autonomy of a UAV for its collision
avoidance when the UAV is teleoperated by a human operator. In
our proposed approach, a teleoperated UAV can not only avoid
collision autonomously with other surrounding objects but also track
the operator’s control input as closely as possible. As a result, an
operator can always be in control of the UAV for his/her high-level
guidance and navigation task without worrying too much about
the UAVs collision avoidance while it is being teleoperated. The
effectiveness of the proposed approach is demonstrated through a
human-in-the-loop simulation of quadrotor UAV teleoperation using
virtual robot experimentation platform (v-rep) and Matlab programs.},
	    journal   = {International Journal of Mechanical and Mechatronics Engineering},
	  volume    = {10},
	  number    = {1},
	  year      = {2016},
	  pages     = {164 - 169},
	  ee        = {https://publications.waset.org/pdf/10003479},
	  url   	= {https://publications.waset.org/vol/109},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 109, 2016},
	}