Tag Archives: Quadcopters

Interesting testing (simulated) bed for quadrotors

Júnio Santos Bulhões, Cristiane Lopes Martins, Cristian Hansen, Márcio Rodrigues da Cunha Reis, Alana da Silva Magalhães, Antonio Paulo Coimbra, Wesley Pacheco Calixto, Platform and simulator with three degrees of freedom for testing quadcopters, Robotics and Autonomous Systems, Volume 176, 2024 DOI: 10.1016/j.robot.2024.104682.

This study aims to design a test platform for quadcopters, which allows the execution of all rotational movements and prevents translational movements without affecting the dynamics of the system. The methodological approach involves both simulation and the construction of the test platform. Two simulators are developed: (i) a linear simulator, used to assist in determining control parameters, and (ii) a nonlinear simulator, used to model the nonlinearity inherent to the rotational behavior of aircraft. In addition, the control system for the quadcopter is implemented, utilizing proportional, integral, and derivative control principles. By conducting seven experiments on the test platform and in the nonlinear simulator, the obtained results are compared in order to validate the proposed methodology. The mean discrepancy observed between the mean absolute difference obtained by the test platform and by the nonlinear simulator for the angle ϕ was 0.85°, for the angle θ was 2.77°, and for the angle ψ was 4.66°. When analyzed separately, the mean absolute errors for the angles, using the nonlinear simulator and the test platform, showed differences below 2% in almost all evaluated experiments. The developed test platform preserves the rotational dynamics of the quadcopter as desired, closely approaching the results obtained by the nonlinear simulator. Consequently, this platform can be used to carry out practical tests in a controlled environment.

Qualitative modelling of quadcopters that is claimed to be better than reinforcement learning

Šoberl, D., Bratko, I. & Žabkar, Learning to Control a Quadcopter Qualitatively., . J Intell Robot Syst 100, 1097–1110 (2020) DOI: 10.1007/s10846-020-01228-7.

Qualitative modeling allows autonomous agents to learn comprehensible control models, formulated in a way that is close to human intuition. By abstracting away certain numerical information, qualitative models can provide better insights into operating principles of a dynamic system in comparison to traditional numerical models. We show that qualitative models, learned from numerical traces, contain enough information to allow motion planning and path following. We demonstrate our methods on the task of flying a quadcopter. A qualitative control model is learned through motor babbling. Training is significantly faster than training times reported in papers using reinforcement learning with similar quadcopter experiments. A qualitative collision-free trajectory is computed by means of qualitative simulation, and executed reactively while dynamically adapting to numerical characteristics of the system. Experiments have been conducted and assessed in the V-REP robotic simulator.

A very detailed study of the performance of propellers

Scanavino, M., Vilardi, A. & Guglieri, G. An Experimental Analysis on Propeller Performance in a Climate-controlled Facility. J Intell Robot Syst 100, 505–517 (2020) DOI: 10.1007/s10846-019-01132-9.

Despite many commercial applications make extensive use of Unmanned Aircraft Systems (UAS), there is still lack of published data about their performance under unconventional weather conditions. In the last years, multirotors and fixed wing vehicles, commonly referred to as drones, have been studied in wind environments so that stability and controllability have been improved. However, other important weather variables have impact on UAS performance and they should be properly investigated for a deeper understanding of such vehicles. The primary objective of our study is the preliminary characterization of a propeller in a climate-controlled chamber. Mechanical and electrical data have been measured while testing the propeller at low pressure and cold temperatures. Test results point out that thrust and electric power are strongly affected by air density. A comparison between the experimental data and the results of the Blade Element Theory is carried out to assess the theory capability to estimate thrust in unconventional environments. The overlap between experimental data and theory computation is appropriate despite geometrical uncertainties and corroborate the need of a reliable aerodynamic database. Propeller performance data under unconventional atmospheres will be leveraged to improve UAS design, propulsion system modelling as well as provide guidelines to certify operations in extreme environments.

Selecting the best visual cues in the next future for reducing the computational cost of localization under limited computational resources

L. Carlone and S. Karaman, Attention and Anticipation in Fast Visual-Inertial Navigation, IEEE Transactions on Robotics, vol. 35, no. 1, pp. 1-20, Feb. 2019 DOI: 10.1109/TRO.2018.2872402.

We study a visual-inertial navigation (VIN) problem in which a robot needs to estimate its state using an on-board camera and an inertial sensor, without any prior knowledge of the external environment. We consider the case in which the robot can allocate limited resources to VIN, due to tight computational constraints. Therefore, we answer the following question: under limited resources, what are the most relevant visual cues to maximize the performance of VIN? Our approach has four key ingredients. First, it is task-driven, in that the selection of the visual cues is guided by a metric quantifying the VIN performance. Second, it exploits the notion of anticipation, since it uses a simplified model for forward-simulation of robot dynamics, predicting the utility of a set of visual cues over a future time horizon. Third, it is efficient and easy to implement, since it leads to a greedy algorithm for the selection of the most relevant visual cues. Fourth, it provides formal performance guarantees: we leverage submodularity to prove that the greedy selection cannot be far from the optimal (combinatorial) selection. Simulations and real experiments on agile drones show that our approach ensures state-of-the-art VIN performance while maintaining a lean processing time. In the easy scenarios, our approach outperforms appearance-based feature selection in terms of localization errors. In the most challenging scenarios, it enables accurate VIN while appearance-based feature selection fails to track robot’s motion during aggressive maneuvers.

Using EKF to estimate the state of a quadcopter in SE(3)

Goodarzi, F.A. & Lee, Global Formulation of an Extended Kalman Filter on SE(3) for Geometric Control of a Quadrotor UAV, J Intell Robot Syst (2017) 88: 395, DOI: 10.1007/s10846-017-0525-6.

An extended Kalman filter (EKF) is developed on the special Euclidean group, S E(3) for geometric control of a quadrotor UAV. It is obtained by performing an intrinsic form of linearization on S E(3) to estimate the state of the quadrotor from noisy measurements. The proposed estimator considers all of the coupling effects between rotational and translational dynamics, and it is developed in a coordinate-free fashion. The desirable features of the proposed EKF are illustrated by numerical examples and experimental results for several scenarios. The proposed estimation scheme on S E(3) has been unprecedented and these results can be particularly useful for aggressive maneuvers in GPS denied environments or in situations where parts of onboard sensors fail.