Autonomous waypoint planning, optimal trajectory generation and nonlinear tracking control for multi-rotor UAVS

Hossein Eslamiat, Yilan Li, Ningshan Wang, Amit Sanyal, Qinru Qiu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A framework for autonomous waypoint planning, trajectory generation through waypoints, and trajectory tracking for multi-rotor unmanned aerial vehicles (UAVs) is proposed in this work. Safe and effective operations of these UAVs is a problem that demands obstacle avoidance strategies and advanced trajectory planning and control schemes for stability and energy efficiency. To address this problem, a two-level optimization strategy is used for trajectory generation, then the trajectory is tracked in a stable manner. The framework given here consists of the following components: (a) a deep reinforcement learning (DRL)-based algorithm for optimal waypoint planning while minimizing control energy and avoiding obstacles in a given environment; (b) an optimal, smooth trajectory generation algorithm through waypoints, that minimizes a combinaton of velocity, acceleration, jerk and snap; and (c) a stable tracking control law that determines a control thrust force for an UAV to track the generated trajectory.

Original languageEnglish (US)
Title of host publication2019 18th European Control Conference, ECC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2695-2700
Number of pages6
ISBN (Electronic)9783907144008
DOIs
StatePublished - Jun 1 2019
Event18th European Control Conference, ECC 2019 - Naples, Italy
Duration: Jun 25 2019Jun 28 2019

Publication series

Name2019 18th European Control Conference, ECC 2019

Conference

Conference18th European Control Conference, ECC 2019
CountryItaly
CityNaples
Period6/25/196/28/19

Fingerprint

Trajectory Generation
Optimal Trajectory
Nonlinear Control
Tracking Control
Rotor
rotors
planning
pilotless aircraft
Rotors
Trajectories
Planning
trajectories
trajectory planning
Trajectory
Unmanned aerial vehicles (UAV)
Trajectory Planning
Obstacle Avoidance
Force Control
Trajectory Tracking
Reinforcement Learning

ASJC Scopus subject areas

  • Instrumentation
  • Control and Optimization

Cite this

Eslamiat, H., Li, Y., Wang, N., Sanyal, A., & Qiu, Q. (2019). Autonomous waypoint planning, optimal trajectory generation and nonlinear tracking control for multi-rotor UAVS. In 2019 18th European Control Conference, ECC 2019 (pp. 2695-2700). [8795855] (2019 18th European Control Conference, ECC 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/ECC.2019.8795855

Autonomous waypoint planning, optimal trajectory generation and nonlinear tracking control for multi-rotor UAVS. / Eslamiat, Hossein; Li, Yilan; Wang, Ningshan; Sanyal, Amit; Qiu, Qinru.

2019 18th European Control Conference, ECC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 2695-2700 8795855 (2019 18th European Control Conference, ECC 2019).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Eslamiat, H, Li, Y, Wang, N, Sanyal, A & Qiu, Q 2019, Autonomous waypoint planning, optimal trajectory generation and nonlinear tracking control for multi-rotor UAVS. in 2019 18th European Control Conference, ECC 2019., 8795855, 2019 18th European Control Conference, ECC 2019, Institute of Electrical and Electronics Engineers Inc., pp. 2695-2700, 18th European Control Conference, ECC 2019, Naples, Italy, 6/25/19. https://doi.org/10.23919/ECC.2019.8795855
Eslamiat H, Li Y, Wang N, Sanyal A, Qiu Q. Autonomous waypoint planning, optimal trajectory generation and nonlinear tracking control for multi-rotor UAVS. In 2019 18th European Control Conference, ECC 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 2695-2700. 8795855. (2019 18th European Control Conference, ECC 2019). https://doi.org/10.23919/ECC.2019.8795855
Eslamiat, Hossein ; Li, Yilan ; Wang, Ningshan ; Sanyal, Amit ; Qiu, Qinru. / Autonomous waypoint planning, optimal trajectory generation and nonlinear tracking control for multi-rotor UAVS. 2019 18th European Control Conference, ECC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 2695-2700 (2019 18th European Control Conference, ECC 2019).
@inproceedings{f0ebb23f731b40c19b19c4166d34b385,
title = "Autonomous waypoint planning, optimal trajectory generation and nonlinear tracking control for multi-rotor UAVS",
abstract = "A framework for autonomous waypoint planning, trajectory generation through waypoints, and trajectory tracking for multi-rotor unmanned aerial vehicles (UAVs) is proposed in this work. Safe and effective operations of these UAVs is a problem that demands obstacle avoidance strategies and advanced trajectory planning and control schemes for stability and energy efficiency. To address this problem, a two-level optimization strategy is used for trajectory generation, then the trajectory is tracked in a stable manner. The framework given here consists of the following components: (a) a deep reinforcement learning (DRL)-based algorithm for optimal waypoint planning while minimizing control energy and avoiding obstacles in a given environment; (b) an optimal, smooth trajectory generation algorithm through waypoints, that minimizes a combinaton of velocity, acceleration, jerk and snap; and (c) a stable tracking control law that determines a control thrust force for an UAV to track the generated trajectory.",
author = "Hossein Eslamiat and Yilan Li and Ningshan Wang and Amit Sanyal and Qinru Qiu",
year = "2019",
month = "6",
day = "1",
doi = "10.23919/ECC.2019.8795855",
language = "English (US)",
series = "2019 18th European Control Conference, ECC 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2695--2700",
booktitle = "2019 18th European Control Conference, ECC 2019",

}

TY - GEN

T1 - Autonomous waypoint planning, optimal trajectory generation and nonlinear tracking control for multi-rotor UAVS

AU - Eslamiat, Hossein

AU - Li, Yilan

AU - Wang, Ningshan

AU - Sanyal, Amit

AU - Qiu, Qinru

PY - 2019/6/1

Y1 - 2019/6/1

N2 - A framework for autonomous waypoint planning, trajectory generation through waypoints, and trajectory tracking for multi-rotor unmanned aerial vehicles (UAVs) is proposed in this work. Safe and effective operations of these UAVs is a problem that demands obstacle avoidance strategies and advanced trajectory planning and control schemes for stability and energy efficiency. To address this problem, a two-level optimization strategy is used for trajectory generation, then the trajectory is tracked in a stable manner. The framework given here consists of the following components: (a) a deep reinforcement learning (DRL)-based algorithm for optimal waypoint planning while minimizing control energy and avoiding obstacles in a given environment; (b) an optimal, smooth trajectory generation algorithm through waypoints, that minimizes a combinaton of velocity, acceleration, jerk and snap; and (c) a stable tracking control law that determines a control thrust force for an UAV to track the generated trajectory.

AB - A framework for autonomous waypoint planning, trajectory generation through waypoints, and trajectory tracking for multi-rotor unmanned aerial vehicles (UAVs) is proposed in this work. Safe and effective operations of these UAVs is a problem that demands obstacle avoidance strategies and advanced trajectory planning and control schemes for stability and energy efficiency. To address this problem, a two-level optimization strategy is used for trajectory generation, then the trajectory is tracked in a stable manner. The framework given here consists of the following components: (a) a deep reinforcement learning (DRL)-based algorithm for optimal waypoint planning while minimizing control energy and avoiding obstacles in a given environment; (b) an optimal, smooth trajectory generation algorithm through waypoints, that minimizes a combinaton of velocity, acceleration, jerk and snap; and (c) a stable tracking control law that determines a control thrust force for an UAV to track the generated trajectory.

UR - http://www.scopus.com/inward/record.url?scp=85071569467&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85071569467&partnerID=8YFLogxK

U2 - 10.23919/ECC.2019.8795855

DO - 10.23919/ECC.2019.8795855

M3 - Conference contribution

AN - SCOPUS:85071569467

T3 - 2019 18th European Control Conference, ECC 2019

SP - 2695

EP - 2700

BT - 2019 18th European Control Conference, ECC 2019

PB - Institute of Electrical and Electronics Engineers Inc.

ER -