414 research outputs found
Design and Autonomous Stabilization of a Ballistically Launched Multirotor
Aircraft that can launch ballistically and convert to autonomous, free flying
drones have applications in many areas such as emergency response, defense, and
space exploration, where they can gather critical situational data using
onboard sensors. This paper presents a ballistically launched, autonomously
stabilizing multirotor prototype (SQUID, Streamlined Quick Unfolding
Investigation Drone) with an onboard sensor suite, autonomy pipeline, and
passive aerodynamic stability. We demonstrate autonomous transition from
passive to vision based, active stabilization, confirming the ability of the
multirotor to autonomously stabilize after a ballistic launch in a GPS denied
environment.Comment: Accepted to 2020 International Conference on Robotics and Automatio
Morphing Concept for Multirotor UAVs Enabling Stability Augmentation and Multiple-Parcel Delivery
This paper presents a novel morphing concept for multirotor Unmanned Aerial Vehicles
(UAVs) to optimize the vehicle
ight performance during multi-parcel deliveries. Abrupt
changes in the vehicle weight distribution during a parcel delivery can cause the UAVs to be
unbalanced. This is usually compensated by the vehicle
ight control system but the motors
may need to operate outside their design range which can deteriorate the stability and
performance of the system. Morphing the geometry of a conventional multirotor airframe
enables the vehicle to continuously re-balanced itself which improves the overall vehicle
performance and safety. The paper derives expressions for the static stability of multirotor
UAVs and discusses the experimental implementation of the morphing technology on a Y6
tricopter configuration. Flight test results of multi-parcel delivery scenarios demonstrate
the capability of the proposed technology to balance the throttle outputs of all rotors
A Survey of Offline and Online Learning-Based Algorithms for Multirotor UAVs
Multirotor UAVs are used for a wide spectrum of civilian and public domain
applications. Navigation controllers endowed with different attributes and
onboard sensor suites enable multirotor autonomous or semi-autonomous, safe
flight, operation, and functionality under nominal and detrimental conditions
and external disturbances, even when flying in uncertain and dynamically
changing environments. During the last decade, given the
faster-than-exponential increase of available computational power, different
learning-based algorithms have been derived, implemented, and tested to
navigate and control, among other systems, multirotor UAVs. Learning algorithms
have been, and are used to derive data-driven based models, to identify
parameters, to track objects, to develop navigation controllers, and to learn
the environment in which multirotors operate. Learning algorithms combined with
model-based control techniques have been proven beneficial when applied to
multirotors. This survey summarizes published research since 2015, dividing
algorithms, techniques, and methodologies into offline and online learning
categories, and then, further classifying them into machine learning, deep
learning, and reinforcement learning sub-categories. An integral part and focus
of this survey are on online learning algorithms as applied to multirotors with
the aim to register the type of learning techniques that are either hard or
almost hard real-time implementable, as well as to understand what information
is learned, why, and how, and how fast. The outcome of the survey offers a
clear understanding of the recent state-of-the-art and of the type and kind of
learning-based algorithms that may be implemented, tested, and executed in
real-time.Comment: 26 pages, 6 figures, 4 tables, Survey Pape
Design and control of next-generation uavs for effectively interacting with environments
In this dissertation, the design and control of a novel multirotor for aerial manipulation is studied, with the aim of endowing the aerial vehicle with more degrees of freedom of motion and stability when interacting with the environments. Firstly, it presents an energy-efficient adaptive robust tracking control method for a class of fully actuated, thrust vectoring unmanned aerial vehicles (UAVs) with parametric uncertainties including unknown moment of inertia, mass and center of mass, which would occur in aerial maneuvering and manipulation. The effectiveness of this method is demonstrated through simulation. Secondly, a humanoid robot arm is adopted to serve as a 6-degree-of-freedom (DOF) automated flight testing platform for emulating the free flight environment of UAVs while ensuring safety. Another novel multirotor in a tilt-rotor architecture is studied and tested for coping with parametric uncertainties in aerial maneuvering and manipulation. Two pairs of rotors are mounted on two independently-controlled tilting arms placed at two sides of the vehicle in a H configuration to enhance its maneuverability and stability through an adaptive robust control method. In addition, an impedance control algorithm is deployed in the out loop that modifies the trajectory to achieve a compliant behavior in the end-effector space for aerial drilling and screwing tasks
Design and Autonomous Stabilization of a Ballistically-Launched Multirotor
Aircraft that can launch ballistically and convert to autonomous, free-flying drones have applications in many areas such as emergency response, defense, and space exploration, where they can gather critical situational data using onboard sensors. This paper presents a ballistically-launched, autonomously-stabilizing multirotor prototype (SQUID - Streamlined Quick Unfolding Investigation Drone) with an onboard sensor suite, autonomy pipeline, and passive aerodynamic stability. We demonstrate autonomous transition from passive to vision-based, active stabilization, confirming the multirotor’s ability to autonomously stabilize after a ballistic launch in a GPS-denied environment
Aerial Manipulation: A Literature Review
Aerial manipulation aims at combining the versatil- ity and the agility of some aerial platforms with the manipulation capabilities of robotic arms. This letter tries to collect the results reached by the research community so far within the field of aerial manipulation, especially from the technological and control point of view. A brief literature review of general aerial robotics and space manipulation is carried out as well
Design and Autonomous Stabilization of a Ballistically-Launched Multirotor
Aircraft that can launch ballistically and convert to autonomous, free-flying drones have applications in many areas such as emergency response, defense, and space exploration, where they can gather critical situational data using onboard sensors. This paper presents a ballistically-launched, autonomously-stabilizing multirotor prototype (SQUID - Streamlined Quick Unfolding Investigation Drone) with an onboard sensor suite, autonomy pipeline, and passive aerodynamic stability. We demonstrate autonomous transition from passive to vision-based, active stabilization, confirming the multirotor’s ability to autonomously stabilize after a ballistic launch in a GPS-denied environment
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