Inversion based direct position control and trajectory following for micro aerial vehicles

Achtelik, Markus; Lynen, Simon; Chli, Margarita; Siegwart, Roland

doi:10.1109/iros.2013.6696772

Cited by 29 publications

(26 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This approach is extended in Faessler, Franchi, and Scaramuzza (2018) to account for first‐order drag effects. Another line of research focuses on nonlinear dynamic inversion, which uses the inverse of the dynamical model and generates a feedforward angular rate command based on a differentiable reference trajectory (M. W. Achtelik, Lynen, Chli, & Siegwart, 2013). The incremental version, incremental nonlinear dynamic inversion, uses stepwise updates of the control input and leads to commands and disturbance rejection on linear and angular acceleration level (Smeur, de Croon, & Chu, 2017).…”

Section: Related Workmentioning

confidence: 99%

ARDEA—An MAV with skills for future planetary missions

Lutz

Müller

Maier

et al. 2020

Journal of Field Robotics

View full text Add to dashboard Cite

We introduce a prototype flying platform for planetary exploration: autonomous robot design for extraterrestrial applications (ARDEA). Communication with unmanned missions beyond Earth orbit suffers from time delay, thus a key criterion for robotic exploration is a robot's ability to perform tasks without human intervention. For autonomous operation, all computations should be done on-board and GlobalNavigation Satellite System (GNSS) should not be relied on for navigation purposes.Given these objectives ARDEA is equipped with two pairs of wide-angle stereo cameras and an inertial measurement unit (IMU) for robust visual-inertial navigation and time-efficient, omni-directional 3D mapping. The four cameras cover a 240 ∘ vertical field of view, enabling the system to operate in confined environments such as caves formed by lava tubes. The captured images are split into several pinhole cameras, which are used for simultaneously running visual odometries. The stereo output is used for simultaneous localization and mapping, 3D map generation and collision-free motion planning. To operate the vehicle efficiently for a variety of missions, ARDEA's capabilities have been modularized into skills which can be assembled to fulfill a mission's objectives. These skills are defined generically so that they are independent of the robot configuration, making the approach suitable for different heterogeneous robotic teams. The diverse skill set also makes the micro aerial vehicle (MAV) useful for any task where autonomous exploration is needed.For example terrestrial search and rescue missions where visual navigation in GNSSdenied indoor environments is crucial, such as partially collapsed man-made structures like buildings or tunnels. We have demonstrated the robustness of our system in indoor and outdoor field tests. K E Y W O R D S aerial robotics, computer vision, exploration, GPS-denied operation, planetary robotics ---This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

show abstract

Section: Related Workmentioning

confidence: 99%

ARDEA—An MAV with skills for future planetary missions

Lutz

Müller

Maier

et al. 2020

Journal of Field Robotics

View full text Add to dashboard Cite

show abstract

“…It is also possible to take a combined approach, where batch estimation is used for some parameters, and a parameter-estimating EKF is run alongside the state estimator to obtain bias-compensated IMU measurements in order to estimate the moments of inertia [7].…”

Section: Related Workmentioning

confidence: 99%

Maximum likelihood parameter identification for MAVs

Burri

Nikolic

Oleynikova

et al. 2016

2016 IEEE International Conference on Robotics and Automation (ICRA)

Self Cite

View full text Add to dashboard Cite

As the applications of Micro Aerial Vehicles (MAVs) get more and more complex, and require highly dynamic motions, it becomes essential to have an accurate dynamic model of the MAV. Such a model can be used for reliable state estimation, control, and for realistic simulation. A good model requires accurate estimates of physical parameters of the system, which we aim to estimate from recorded flight data. In this paper, we present a detailed physical model of the MAV and a maximum likelihood estimation scheme for determining the dominant parameters, such as inertia matrix, center of gravity (CoG) with respect to the IMU, and parameters related to the aerodynamics. To incorporate all information given by the IMU and the physical MAV model, we propose to use two process models in the optimization. We show the effectiveness of the method on simulated data, as well as on a real platform.

show abstract

“…In flight control of MAVs of similar dynamics-quadrotors, it is common to divide a controller into an inner loop and an outer loop [11], [12], [13]. This also applies to our previous work in [10].…”

Section: Introductionmentioning

confidence: 99%

Single-loop control and trajectory following of a flapping-wing microrobot

Chirarattananon

Kevin

Wood

2014

2014 IEEE International Conference on Robotics and Automation (ICRA)

View full text Add to dashboard Cite

Abstract-Inspired by the agility of flying insects and the recent development on an insect-scale aerial vehicle, we propose a single-loop adaptive flight control suite designed with an emphasis on the ability to track dynamic trajectories as a step towards the goal of performing acrobatic maneuvers as observed in real insects. Instead of the conventional approach of having cascaded control loops, the proposed controller directly regulates the commanded torques to stabilize the attitude and lateral position in a single loop. One of the recent successful prototypes from the RoboBees project demonstrated its first unconstrained flight [6]. The 80mg Micro Aerial Vehicle (MAV) shown in figure 1 is a result of the culmination of research in meso-scale actuation and manufacturing technology [7], [8]. The flappingwing robot is able to generate body torques and sufficient lift force [9] satisfying the key requirements for stable flight with the aid of an active flight controller [6].In an effort to improve the flight performance demonstrated in [6], the lack of comprehensive knowledge of the system and variation caused by imperfect fabrication motivated the development of a suite of adaptive flight controller capable of coping with model uncertainties [10]. This brought about marked improvement in flight performance as evidenced by a reduction in position errors, particularly for hovering flights. Moreover, the fidelity of this flight controller was further demonstrated in vertical takeoff and landing flights.

show abstract

Inversion based direct position control and trajectory following for micro aerial vehicles

Cited by 29 publications

References 12 publications

ARDEA—An MAV with skills for future planetary missions

ARDEA—An MAV with skills for future planetary missions

Maximum likelihood parameter identification for MAVs

Single-loop control and trajectory following of a flapping-wing microrobot

Contact Info

Product

Resources

About