14 research outputs found
The Phoenix Drone: An Open-Source Dual-Rotor Tail-Sitter Platform for Research and Education
In this paper, we introduce the Phoenix drone: the first completely
open-source tail-sitter micro aerial vehicle (MAV) platform. The vehicle has a
highly versatile, dual-rotor design and is engineered to be low-cost and easily
extensible/modifiable. Our open-source release includes all of the design
documents, software resources, and simulation tools needed to build and fly a
high-performance tail-sitter for research and educational purposes. The drone
has been developed for precision flight with a high degree of control
authority. Our design methodology included extensive testing and
characterization of the aerodynamic properties of the vehicle. The platform
incorporates many off-the-shelf components and 3D-printed parts, in order to
keep the cost down. Nonetheless, the paper includes results from flight trials
which demonstrate that the vehicle is capable of very stable hovering and
accurate trajectory tracking. Our hope is that the open-source Phoenix
reference design will be useful to both researchers and educators. In
particular, the details in this paper and the available open-source materials
should enable learners to gain an understanding of aerodynamics, flight
control, state estimation, software design, and simulation, while experimenting
with a unique aerial robot.Comment: In Proceedings of the IEEE International Conference on Robotics and
Automation (ICRA'19), Montreal, Canada, May 20-24, 201
Micro and macro quadcopter drones for indoor mapping to support disaster management
In this paper we present the operations and mapping techniques of two drones that are different in terms of size, the sensors deployed, and the positioning and mapping techniques used. The first drone is a low-cost commercial quadcopter microdrone, a Crazyflie, while the second drone is a relatively expensive research quadcopter macrodrone, called MAX. We investigated their feasibility in mapping areas where satellite positioning is not available, such as indoor spaces
Signal-based self-organization of a chain of UAVs for subterranean exploration
Miniature multi-rotors are promising robots for navigating subterranean
networks, but maintaining a radio connection underground is challenging. In
this paper, we introduce a distributed algorithm, called U-Chain (for
Underground-chain), that coordinates a chain of flying robots between an
exploration drone and an operator. Our algorithm only uses the measurement of
the signal quality between two successive robots as well as an estimate of the
ground speed based on an optic flow sensor. We evaluate our approach formally
and in simulation, and we describe experimental results with a chain of 3 real
miniature quadrotors (12 by 12 cm) and a base station
UWB-based system for UAV Localization in GNSS-Denied Environments: Characterization and Dataset
Small unmanned aerial vehicles (UAV) have penetrated multiple domains over
the past years. In GNSS-denied or indoor environments, aerial robots require a
robust and stable localization system, often with external feedback, in order
to fly safely. Motion capture systems are typically utilized indoors when
accurate localization is needed. However, these systems are expensive and most
require a fixed setup. Recently, visual-inertial odometry and similar methods
have advanced to a point where autonomous UAVs can rely on them for
localization. The main limitation in this case comes from the environment, as
well as in long-term autonomy due to accumulating error if loop closure cannot
be performed efficiently. For instance, the impact of low visibility due to
dust or smoke in post-disaster scenarios might render the odometry methods
inapplicable. In this paper, we study and characterize an ultra-wideband (UWB)
system for navigation and localization of aerial robots indoors based on
Decawave's DWM1001 UWB node. The system is portable, inexpensive and can be
battery powered in its totality. We show the viability of this system for
autonomous flight of UAVs, and provide open-source methods and data that enable
its widespread application even with movable anchor systems. We characterize
the accuracy based on the position of the UAV with respect to the anchors, its
altitude and speed, and the distribution of the anchors in space. Finally, we
analyze the accuracy of the self-calibration of the anchors' positions.Comment: Accepted to the 2020 IEEE/RSJ International Conference on Intelligent
Robots and Systems (IROS 2020