Quadrotor Helicopter Trajectory Tracking Control

By G. Hoffmann, Steven L. Waslander, Claire Jennifer Tomlin. 2008

371 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/36515a1049836e095ca192424bfd59e1501ce9cd

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In Computer Vision and Pattern Recognition

In Control and Systems Engineering

Citations in the corpus

The GRASP Multiple Micro-UAV Testbed (2010, background): “Similar nesting of control loops is presented in previous works [5] –[7] [16] [17].”
A computationally efficient algorithm for state-to-state quadrocopter trajectory generation and feasibility verification (2013, background): “Broadly speaking, a first group of algorithms handles the trajectory problem by decoupling geometric and temporal planning: in a first step, a geometric trajectory without time information is constructed, for example using lines [8], polynomials [2], or splines [9].”
Design, modeling, estimation and control for aerial grasping and manipulation (2011, background): “None of this previous work, however, considers the changes in flight dynamics due to the grasped payload. b) Quadrotor Control: Quadrotor control has been widely addressed in the literature from basic hovering and trajectory following [8], [4] to aggressive and aerobatic maneuvers [12], [13] .”
Minimum snap trajectory generation and control for quadrotors (2011, methodology): “Most of the work in this area uses controllers that are derived from linearization of the model around hover conditions and are stable only under reasonably small roll and pitch angles [5].”
A Computationally Efficient Motion Primitive for Quadrocopter Trajectory Generation (2015, background): “Broadly speaking, a first group of algorithms handles the trajectory generation problem by decoupling geometric and temporal planning: In a first step, a geometric trajectory without time information is constructed, for example, using lines [6], polynomials [7], or splines [8].”
Cooperative Grasping and Transport Using Multiple Quadrotors (2010, methodology): “We use an approach similar to those described in [13, 12].”
Provably safe and robust learning-based model predictive control (2011, methodology): “If the system has SE [41,34,49], then the control law of the LBMPC with oracle (13) converges in probability to the control law of an MPC that knows the true model (i.e.,”
Differential flatness based control of a rotorcraft for aggressive maneuvers (2011, methodology): “[4] implemented a path planning and control method that specifically avoided utilizing feed-forward control.”
Trajectory generation and control for precise aggressive maneuvers with quadrotors (2012, methodology): “We use an approach similar to that described by Hoffmann et al. (2008) but extend it from 2D to 3D trajectories.”