Learning quadrotor maneuvers from optimal control and generalizing in real-time

Tomić, Teodor; Maier, Moritz; Haddadin, Sami

doi:10.1109/icra.2014.6907087

Cited by 24 publications

(14 citation statements)

References 29 publications

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“…We experimented with SNN with more hidden layers or more neurons in the hidden layer, but they result in similar or larger test error. Specifically, MLPs of size (2,50,20,75) and (2,20,50,75), (2,30,30,30,75) yield test errors of 0.258, 0.170, and 0.232, respectively. The size (2, 300, 75) network, on the other hand, has test error of 0.058.…”

Section: E Discussion and Preliminary Experimentationmentioning

confidence: 99%

Discontinuity-Sensitive Optimal Control Learning by Mixture of Experts

Tang

Hauser

2019

2019 International Conference on Robotics and Automation (ICRA)

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This paper proposes a discontinuity-sensitive approach to learn the solutions of parametric optimal control problems with high accuracy. Many tasks, ranging from model predictive control to reinforcement learning, may be solved by learning optimal solutions as a function of problem parameters. However, nonconvexity, discrete homotopy classes, and control switching cause discontinuity in the parameter-solution mapping, thus making learning difficult for traditional continuous function approximators. A mixture of experts (MoE) model composed of a classifier and several regressors is proposed to address such an issue. The optimal trajectories of different parameters are clustered such that in each cluster the trajectories are continuous function of problem parameters. Numerical examples on benchmark problems show that training the classifier and regressors individually outperforms joint training of MoE. With suitably chosen clusters, this approach not only achieves lower prediction error with less training data and fewer model parameters, but also leads to dramatic improvements in the reliability of trajectory tracking compared to traditional universal function approximation models (e.g., neural networks).

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Section: E Discussion and Preliminary Experimentationmentioning

confidence: 99%

Discontinuity-Sensitive Optimal Control Learning by Mixture of Experts

Tang

Hauser

2019

2019 International Conference on Robotics and Automation (ICRA)

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“…The application of aerial manipulation robots to inspection and maintenance operations [1] in industrial scenarios like oil and gas refineries [2] [3], wind turbines [4], or bridges [5] [6] is motivated by the convenience to reduce the required time and cost with respect to conventional solutions carried out nowadays by human operators deployed on cranes and other infrastructures. The ability of multirotors [7] [8] and autonomous helicopters [9][10] to reach quickly and easily high altitude workspaces [11] [12] [13] can be useful in the installation [14] [15] and retrieval [14] [16] of sensors devices in polluted areas, transportation operations [17], inspection by contact [18] [19], crack repair [20], valve turning [21] and other torsional manipulation tasks [22], or in those tasks requiring the use of tools [23].…”

Section: Introductionmentioning

confidence: 99%

Aerial Manipulator With Rolling Base for Inspection of Pipe Arrays

Suárez¹,

Caballero²,

Garofano³

et al. 2020

IEEE Access

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This paper considers the inspection by contact of long arrays of pipe structures in hard-to-reach places, typical of chemical plants or oil and gas industries, presenting the design of a hybrid rolling-aerial platform capable of landing and moving along the pipes without wasting energy in the propellers during the inspection. The presented robot overcomes the limitation in terms of operation time and positioning accuracy in the application of flying robots to industrial inspection and maintenance tasks. The robot consists of a hexarotor platform integrating a rolling base with velocity and direction control, and a 5-DOF (degree of freedom) robotic arm supported by a 1-DOF linear guide system that facilitates the deployment of the arm in the array of pipes to inspect their contour once the platform has landed. Given a set of points to be inspected in different arrays of pipes, the path of the multirotor and the rolling platform is planned with a hybrid RRT* (Rapidlyexploring Random Tree) based algorithm that minimizes the energy consumption. The performance of the system is evaluated in an illustrative outdoor scenario with two arrays of pipes, using a laser tracking system to measure the position of the robot from the ground control station.

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“…Furthermore, in Reference 4, a method for learning and online generalization of maneuvers for quadrotor‐type vehicles was presented. The maneuvers were formulated as continuous optimal control problems, and the optimal solutions were encoded and generalized with dynamic movement primitives.…”

Section: Introductionmentioning

confidence: 99%

Finite horizon nonlinear optimal control for a quadrotor: Experimental results

Santos‐Sánchez¹,

García²,

Romero³

et al. 2020

Optim Control Appl Methods

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SummaryIn this article, a suboptimal nonlinear discrete control sequence for nonlinear discrete affine control systems is proposed. Using the dynamic programming approach in discrete time domain, the suboptimal control sequence is obtained in every step considering a quadratic performance index of finite horizon. The proposed control strategy is applied to improve the dynamic and energetic performances of a quadrotor unmanned aerial vehicle, when it is subject to special maneuvers or flight conditions, such as the take off and landing phases or trajectory tracking. For these tasks, it could be required convergence in finite time and good behavior. Performing a comparative experimental study with others controllers (optimal linear and PD controllers), the effectiveness of proposed approach is proven.

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Learning quadrotor maneuvers from optimal control and generalizing in real-time

Cited by 24 publications

References 29 publications

Discontinuity-Sensitive Optimal Control Learning by Mixture of Experts

Discontinuity-Sensitive Optimal Control Learning by Mixture of Experts

Aerial Manipulator With Rolling Base for Inspection of Pipe Arrays

Finite horizon nonlinear optimal control for a quadrotor: Experimental results

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