Polynomial Trajectory Planning for Aggressive Quadrotor Flight in Dense Indoor Environments. An, B., Zhang, T., Yuan, C., & Cui, K. Cailiao Yanjiu Xuebao/Chinese Journal of Materials Research, 17(5):459–465, 2013. ![Polynomial Trajectory Planning for Aggressive Quadrotor Flight in Dense Indoor Environments [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper abstract bibtex We explore the challenges of planning trajectories for quadrotors through cluttered indoor environments. We extend the existing work on polynomial trajec- tory generation by presenting a method of jointly optimizing polynomial path seg- ments in an unconstrained quadratic program that is numerically stable for high- order polynomials and large numbers of segments, and is easily formulated for ef- ficient sparse computation.We also present a technique for automatically selecting the amount of time allocated to each segment, and hence the quadrotor speeds along the path, as a function of a single parameter determining aggressiveness, subject to actuator constraints. The use of polynomial trajectories, coupled with the differen- tially flat representation of the quadrotor, eliminates the need for computationally intensive sampling and simulation in the high dimensional state space of the vehi- cle during motion planning. Our approach generates high-quality trajectories much faster than purely sampling-based optimal kinodynamic planning methods, but sac- rifices the guarantee of asymptotic convergence to the global optimum that those methods provide. We demonstrate the performance of our algorithm by efficiently generating trajectories through challenging indoor spaces and successfully travers- ing them at speeds up to 8 m/s. A demonstration of our algorithm and flight perfor- mance is available at: http://groups.csail.mit.edu/rrg/quad_polynomial_ trajectory_planning.
@article{An2013,
abstract = {We explore the challenges of planning trajectories for quadrotors through cluttered indoor environments. We extend the existing work on polynomial trajec- tory generation by presenting a method of jointly optimizing polynomial path seg- ments in an unconstrained quadratic program that is numerically stable for high- order polynomials and large numbers of segments, and is easily formulated for ef- ficient sparse computation.We also present a technique for automatically selecting the amount of time allocated to each segment, and hence the quadrotor speeds along the path, as a function of a single parameter determining aggressiveness, subject to actuator constraints. The use of polynomial trajectories, coupled with the differen- tially flat representation of the quadrotor, eliminates the need for computationally intensive sampling and simulation in the high dimensional state space of the vehi- cle during motion planning. Our approach generates high-quality trajectories much faster than purely sampling-based optimal kinodynamic planning methods, but sac- rifices the guarantee of asymptotic convergence to the global optimum that those methods provide. We demonstrate the performance of our algorithm by efficiently generating trajectories through challenging indoor spaces and successfully travers- ing them at speeds up to 8 m/s. A demonstration of our algorithm and flight perfor- mance is available at: http://groups.csail.mit.edu/rrg/quad_polynomial_ trajectory_planning.},
author = {An, Bing and Zhang, Tongjun and Yuan, Chao and Cui, Kun},
file = {:C\:/Users/robodd/Desktop/FYP_Final Report_Ziniu Wu/ref/RR13_Roy_Polynomial trajectory.pdf:pdf},
isbn = {9783319288727},
issn = {10053093},
journal = {Cailiao Yanjiu Xuebao/Chinese Journal of Materials Research},
keywords = {Ag/Cu thin film,Annealing residual stress,Deformation mechanism maps,Metallic materials},
number = {5},
pages = {459--465},
title = {{Polynomial Trajectory Planning for Aggressive Quadrotor Flight in Dense Indoor Environments}},
url = {https://link.springer.com/chapter/10.1007/978-3-319-28872-7_37},
volume = {17},
year = {2013}
}
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