Perception-aware time optimal path parameterization for quadrotors

© 2020 IEEE. The increasing popularity of quadrotors has given rise to a class of predominantly vision-driven vehicles. This paper addresses the problem of perception-aware time optimal path parametrization for quadrotors. Although many different choices of perceptual modalities are available, the l...

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Bibliographic Details
Main Authors: Spasojevic, Igor (Author), Murali, Varun (Author), Karaman, Sertac (Author)
Other Authors: Massachusetts Institute of Technology. Department of Aeronautics and Astronautics (Contributor), Massachusetts Institute of Technology. Laboratory for Information and Decision Systems (Contributor)
Format: Article
Language:English
Published: IEEE, 2021-12-14T16:27:37Z.
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Online Access:Get fulltext
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100 1 0 |a Spasojevic, Igor  |e author 
100 1 0 |a Massachusetts Institute of Technology. Department of Aeronautics and Astronautics  |e contributor 
100 1 0 |a Massachusetts Institute of Technology. Laboratory for Information and Decision Systems  |e contributor 
700 1 0 |a Murali, Varun  |e author 
700 1 0 |a Karaman, Sertac  |e author 
245 0 0 |a Perception-aware time optimal path parameterization for quadrotors 
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520 |a © 2020 IEEE. The increasing popularity of quadrotors has given rise to a class of predominantly vision-driven vehicles. This paper addresses the problem of perception-aware time optimal path parametrization for quadrotors. Although many different choices of perceptual modalities are available, the low weight and power budgets of quadrotor systems makes a camera ideal for on-board navigation and estimation algorithms. However, this does come with a set of challenges. The limited field of view of the camera can restrict the visibility of salient regions in the environment, which dictates the necessity to consider perception and planning jointly. The main contribution of this paper is an efficient time optimal path parametrization algorithm for quadrotors with limited field of view constraints. We show in a simulation study that a state-of-the-art controller can track planned trajectories, and we validate the proposed algorithm on a quadrotor platform in experiments. 
546 |a en 
655 7 |a Article 
773 |t 10.1109/icra40945.2020.9197157 
773 |t Proceedings - IEEE International Conference on Robotics and Automation