1,403 research outputs found
A modular software architecture for UAVs
There have been several attempts to create scalable and hardware independent software architectures for Unmanned Aerial Vehicles (UAV). In this work, we propose an onboard architecture for UAVs where hardware abstraction, data storage and communication between modules are efficiently maintained. All processing and software development is done on the UAV while state and mission status of the UAV is monitored from a ground station. The architecture also allows rapid development of mission-specific third party applications on the vehicle with the help of the core module
Implementation of UAV Coordination Based on a Hierarchical Multi-UAV Simulation Platform
In this paper, a hierarchical multi-UAV simulation platform,called XTDrone,
is designed for UAV swarms, which is completely open-source 4 . There are six
layers in XTDrone: communication, simulator,low-level control, high-level
control, coordination, and human interac-tion layers. XTDrone has three
advantages. Firstly, the simulation speedcan be adjusted to match the computer
performance, based on the lock-step mode. Thus, the simulations can be
conducted on a work stationor on a personal laptop, for different purposes.
Secondly, a simplifiedsimulator is also developed which enables quick algorithm
designing sothat the approximated behavior of UAV swarms can be observed
inadvance. Thirdly, XTDrone is based on ROS, Gazebo, and PX4, andhence the
codes in simulations can be easily transplanted to embeddedsystems. Note that
XTDrone can support various types of multi-UAVmissions, and we provide two
important demos in this paper: one is aground-station-based multi-UAV
cooperative search, and the other is adistributed UAV formation flight,
including consensus-based formationcontrol, task assignment, and obstacle
avoidance.Comment: 12 pages, 10 figures. And for the, see
https://gitee.com/robin_shaun/XTDron
LAVAPilot: Lightweight UAV Trajectory Planner with Situational Awareness for Embedded Autonomy to Track and Locate Radio-tags
Tracking and locating radio-tagged wildlife is a labor-intensive and
time-consuming task necessary in wildlife conservation. In this article, we
focus on the problem of achieving embedded autonomy for a resource-limited
aerial robot for the task capable of avoiding undesirable disturbances to
wildlife. We employ a lightweight sensor system capable of simultaneous (noisy)
measurements of radio signal strength information from multiple tags for
estimating object locations. We formulate a new lightweight task-based
trajectory planning method-LAVAPilot-with a greedy evaluation strategy and a
void functional formulation to achieve situational awareness to maintain a safe
distance from objects of interest. Conceptually, we embed our intuition of
moving closer to reduce the uncertainty of measurements into LAVAPilot instead
of employing a computationally intensive information gain based planning
strategy. We employ LAVAPilot and the sensor to build a lightweight aerial
robot platform with fully embedded autonomy for jointly tracking and planning
to track and locate multiple VHF radio collar tags used by conservation
biologists. Using extensive Monte Carlo simulation-based experiments,
implementations on a single board compute module, and field experiments using
an aerial robot platform with multiple VHF radio collar tags, we evaluate our
joint planning and tracking algorithms. Further, we compare our method with
other information-based planning methods with and without situational awareness
to demonstrate the effectiveness of our robot executing LAVAPilot. Our
experiments demonstrate that LAVAPilot significantly reduces (by 98.5%) the
computational cost of planning to enable real-time planning decisions whilst
achieving similar localization accuracy of objects compared to information gain
based planning methods, albeit taking a slightly longer time to complete a
mission.Comment: Accepted to 2020 IEEE/RSJ International Conference on Intelligent
Robots and Systems (IROS
Carnegie Mellon Team Tartan: Mission-level Robustness with Rapidly Deployed Autonomous Aerial Vehicles in the MBZIRC 2020
For robotics systems to be used in high risk, real-world situations, they
have to be quickly deployable and robust to environmental changes,
under-performing hardware, and mission subtask failures. Robots are often
designed to consider a single sequence of mission events, with complex
algorithms lowering individual subtask failure rates under some critical
constraints. Our approach is to leverage common techniques in vision and
control and encode robustness into mission structure through outcome monitoring
and recovery strategies, aided by a system infrastructure that allows for quick
mission deployments under tight time constraints and no central communication.
We also detail lessons in rapid field robotics development and testing. Systems
were developed and evaluated through real-robot experiments at an outdoor test
site in Pittsburgh, Pennsylvania, USA, as well as in the 2020 Mohamed Bin Zayed
International Robotics Challenge. All competition trials were completed in
fully autonomous mode without RTK-GPS. Our system led to 4th place in Challenge
2 and 7th place in the Grand Challenge, and achievements like popping five
balloons (Challenge 1), successfully picking and placing a block (Challenge 2),
and dispensing the most water autonomously with a UAV of all teams onto an
outdoor, real fire (Challenge 3).Comment: 28 pages, 26 figures. To appear in Field Robotics, Special Issues on
MBZIRC 202
Research Brief
Approved for public release; distribution is unlimited
MRS Drone: A Modular Platform for Real-World Deployment of Aerial Multi-Robot Systems
This paper presents a modular autonomous Unmanned Aerial Vehicle (UAV)
platform called the Multi-robot Systems (MRS) Drone that can be used in a large
range of indoor and outdoor applications. The MRS Drone features unique
modularity with respect to changes in actuators, frames, and sensory
configuration. As the name suggests, the platform is specially tailored for
deployment within a MRS group. The MRS Drone contributes to the
state-of-the-art of UAV platforms by allowing smooth real-world deployment of
multiple aerial robots, as well as by outperforming other platforms with its
modularity. For real-world multi-robot deployment in various applications, the
platform is easy to both assemble and modify. Moreover, it is accompanied by a
realistic simulator to enable safe pre-flight testing and a smooth transition
to complex real-world experiments. In this manuscript, we present mechanical
and electrical designs, software architecture, and technical specifications to
build a fully autonomous multi UAV system. Finally, we demonstrate the full
capabilities and the unique modularity of the MRS Drone in various real-world
applications that required a diverse range of platform configurations.Comment: 49 pages, 39 figures, accepted for publication to the Journal of
Intelligent & Robotic System
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