1,158 research outputs found
Remote ID for separation provision and multi-agent navigation
In this paper, we investigate the integration of drone identification data
(Remote ID) with collision avoidance mechanisms to improve the safety and
efficiency of multi-drone operations. We introduce an improved Near Mid-Air
Collision (NMAC) definition, termed as UAV NMAC (uNMAC), which accounts for
uncertainties in the drone's location due to self-localization errors and
possible displacements between two location reports. Our proposed uNMAC-based
Reciprocal Velocity Obstacle (RVO) model integrates Remote ID messages with RVO
to enable enhanced collision-free navigation. We propose modifications to the
Remote ID format to include data on localization accuracy and drone airframe
size, facilitating more efficient collision avoidance decisions. Through
extensive simulations, we demonstrate that our approach halves mission
execution times compared to a conservative standard Remote ID-based RVO.
Importantly, it ensures collision-free operations even under localization
uncertainties. By integrating the improved Remote ID messages and uNMAC-based
RVO, we offer a solution to significantly increase airspace capacity while
adhering to strict safety standards. Our study emphasizes the potential to
augment the safety and efficiency of future drone operations, thereby
benefiting industries reliant on drone technologies.Comment: 10 pages, 8 figures, 2023 IEEE/AIAA 42nd Digital Avionics Systems
Conference (DASC
Fly, Wake-up, Find: UAV-based Energy-efficient Localization for Distributed Sensor Nodes
A challenging application scenario in the field of industrial Unmanned Aerial Vehicles (UAVs) is the capability of a robot to find and query smart sensor nodes deployed at arbitrary locations in the mission area. This work explores the combination of different communication technologies, namely, Ultra-Wideband (UWB) and Wake-Up Radio (WUR), with a UAV that acts as a "ubiquitous local-host"of a Wireless Sensor Network (WSN). First, the UAV performs the localization of the sensor node via multiple UWB range measurements, and then it flies in its proximity to perform energy-efficient data acquisition. We propose an energy-efficient and accurate localization algorithm - based on multi-lateration - that is computationally inexpensive and robust to in-field noise. Aiming at minimizing the sensor node energy consumption, we also present a communication protocol that leverages WUR technology to minimize ON-time of the power-hungry UWB transceiver on the sensors. In-field experimental evaluation demonstrates that our approach achieves a sub-meter localization precision of the sensor nodes - i.e., down to 0.6 m - using only three range measurements, and runs in 4 ms on a low power microcontroller (ARM Cortex-M4F). Due to the presence of the WUR and the proposed lightweight algorithm, the entire localization-acquisition cycle requires only 31 mJ on the sensor node. The approach is suitable for several emerging Industrial Internet of Things application scenarios where a mobile vehicle needs to estimate the location of static objects without any precise knowledge of their position
Dynamic Landing of an Autonomous Quadrotor on a Moving Platform in Turbulent Wind Conditions
Autonomous landing on a moving platform presents unique challenges for
multirotor vehicles, including the need to accurately localize the platform,
fast trajectory planning, and precise/robust control. Previous works studied
this problem but most lack explicit consideration of the wind disturbance,
which typically leads to slow descents onto the platform. This work presents a
fully autonomous vision-based system that addresses these limitations by
tightly coupling the localization, planning, and control, thereby enabling fast
and accurate landing on a moving platform. The platform's position,
orientation, and velocity are estimated by an extended Kalman filter using
simulated GPS measurements when the quadrotor-platform distance is large, and
by a visual fiducial system when the platform is nearby. The landing trajectory
is computed online using receding horizon control and is followed by a boundary
layer sliding controller that provides tracking performance guarantees in the
presence of unknown, but bounded, disturbances. To improve the performance, the
characteristics of the turbulent conditions are accounted for in the
controller. The landing trajectory is fast, direct, and does not require
hovering over the platform, as is typical of most state-of-the-art approaches.
Simulations and hardware experiments are presented to validate the robustness
of the approach.Comment: 7 pages, 8 figures, ICRA2020 accepted pape
CoBe -- Coded Beacons for Localization, Object Tracking, and SLAM Augmentation
This paper presents a novel beacon light coding protocol, which enables fast
and accurate identification of the beacons in an image. The protocol is
provably robust to a predefined set of detection and decoding errors, and does
not require any synchronization between the beacons themselves and the optical
sensor. A detailed guide is then given for developing an optical tracking and
localization system, which is based on the suggested protocol and readily
available hardware. Such a system operates either as a standalone system for
recovering the six degrees of freedom of fast moving objects, or integrated
with existing SLAM pipelines providing them with error-free and easily
identifiable landmarks. Based on this guide, we implemented a low-cost
positional tracking system which can run in real-time on an IoT board. We
evaluate our system's accuracy and compare it to other popular methods which
utilize the same optical hardware, in experiments where the ground truth is
known. A companion video containing multiple real-world experiments
demonstrates the accuracy, speed, and applicability of the proposed system in a
wide range of environments and real-world tasks. Open source code is provided
to encourage further development of low-cost localization systems integrating
the suggested technology at its navigation core
Multitrajectory Model Predictive Control for Safe UAV Navigation in an Unknown Environment
The problem of navigating an unmanned aerial vehicle (UAV) in an unknown environment is addressed with a novel model predictive control (MPC) formulation, named multitrajectory MPC (mt-MPC). The objective is to safely drive the vehicle to the desired target location by relying only on the partial description of the surroundings provided by an exteroceptive sensor. This information results in time-varying constraints during the navigation among obstacles. The proposed mt-MPC generates a sequence of position set points that are fed to control loops at lower hierarchical levels. To do so, the mt-MPC predicts two different state trajectories, a safe one and an exploiting one, in the same finite horizon optimal control problem (FHOCP). This formulation, particularly suitable for problems with uncertain time-varying constraints, allows one to partially decouple constraint satisfaction (safety) from cost function minimization (exploitation). Uncertainty due to modeling errors and sensors noise is taken into account as well, in a set membership (SM) framework. Theoretical guarantees of persistent obstacle avoidance are derived under suitable assumptions, and the approach is demonstrated experimentally out-of-the-laboratory on a prototype built with off-the-shelf components
An assessment on the use of stationary vehicles to support cooperative positioning systems
In this paper, we evaluate the ability of stationary vehicles (e.g. parked or temporary stopped cars) as tools to enhance the capabilities of existing cooperative positioning algorithms in vehicular networks. First, some real-world facts are provided to support the feasibility of our ideas. Then, we examine the idea in greater details in terms of the technical requirements and methodological analysis, and provide a comprehensive experimental evaluation using dedicated simulations. The routing of a drone through an urban scenario is presented as a non-traditional application case, where the benefits of the proposed approach are reflected in a better utilisation of the flight time
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