Localizing radio frequency (RF) sources with an unmanned aerial vehicle (UAV) has many important applications. As a result, UAV-based localization has been the focus of much research. However, previous approaches rely heavily on custom electronics and specialized knowledge, are not robust and require extensive calibration, or are inefficient with measurements and waste energy on a battery-constrained platform. In this work, we present a system based on a multirotor UAV that addresses these shortcomings. Our system measures signal strength received by two antennas to update a probability distribution over possible transmitter locations. An information-theoretic controller is used to direct the UAV's search. Signal strength is measured with low-cost, commercial-off-the-shelf components. We demonstrate our system using three transmitters: a continuous signal in the UHF band, a wildlife collar pulsing in the VHF band, and a cell phone making a voice call over LTE. Our system significantly outperforms previous methods, localizing the RF source in the same time it takes previous methods to make a single measurement.
We present SMORS, the first Soft fully actuated MultirOtoR System for multimodal locomotion. Unlike conventional hexarotors, SMORS is equipped with three rigid and three continuously soft arms, with each arm hosting a propeller. We create a bridge between the fields of soft and aerial robotics by mechanically coupling the actuation of a fully actuated flying platform with the actuation of a soft robotic manipulator. Each rotor is slightly tilted, allowing for full actuation of the platform. The soft components combined with the platform's full actuation allow for a robust interaction, in the f…
Defence Research and Development Canada（加拿大国防研究与发展部）；University of Toronto Institute for Aerospace Studies (UTIAS), University of Toronto（多伦多大学多伦多航空航天研究所（UTIAS））
Redundant navigation systems are critical for safe operation of UAVs in high-risk environments. Since most commercial UAVs almost wholly rely on GPS, jamming, interference and multi-pathing are real concerns that usually limit their operations to low-risk environments and Visual Line-Of-Sight. This paper presents a vision-based route-following system for the autonomous, safe return of UAVs under primary navigation failure such as GPS jamming. Using a Visual Teach & Repeat framework to build a visual map of the environment during an outbound flight, we show the autonomous return of the UAV by v…
This paper presents a new method for integrated time-optimal routing and trajectory optimization of multirotor unmanned aerial vehicles (UAVs). Our approach extends the well-known Traveling Salesman Problem by accounting for the limited maneuverability of the UAVs due to their kinematic properties. To this end, we allow each waypoint to be traversed with a discretized velocity as well as a discretized flight direction and compute time-optimal trajectories to determine the travel time costs for each edge. We refer to this novel optimization problem as the Trajectory-based Traveling Salesman Pro…
In many unmanned aerial vehicle (UAV) applications for surveillance and data collection, it is not possible to reach all requested locations due to the given maximum flight time. Hence, the requested locations must be prioritized and the problem of selecting the most important locations is modeled as an Orienteering Problem (OP). To fully exploit the kinematic properties of the UAV in such scenarios, we combine the OP with the generation of time-optimal trajectories with bounds on velocity and acceleration. We define the resulting problem as the Kinematic Orienteering Problem (KOP) and propose…
An Experimental Study of Downwash Effects on a Continuum Manipulator Integrated with a Multirotor UAV
Queensland University of Technology (QUT)（昆士兰科技大学）；QUT Centre for Robotics（昆士兰科技大学机器人中心）；Research Engineering Facility (REF)（研究工程设施）；School of Electrical Engineering and Robotics（电气工程与机器人学院）
The demand for accurate and fast trajectory tracking for multirotor Unmanned Aerial Vehicles (UAVs) have grown recently due to advances in UAV avionics technology and application domains. In many applications, the multirotor UAV is required to accurately perform aggressive maneuvers in challenging scenarios like the presence of external wind disturbances or in-flight payload changes. In this paper, we propose a systematic controller tuning approach based on identification results obtained by a recently developed Deep Neural Networks with the Modified Relay Feedback Test (DNN-MRFT) algorithm. W…
Unmanned aerial vehicles (UAVs) are finding use in applications that place increasing emphasis on robustness to external disturbances including extreme wind. However, traditional multirotor UAV platforms do not directly sense wind; conventional flow sensors are too slow, insensitive, or bulky for widespread integration on UAVs. Instead, drones typically observe the effects of wind indirectly through accumulated errors in position or trajectory tracking. In this work, we integrate a novel flow sensor based on micro-electro-mechanical systems (MEMS) hot-wire technology developed in our prior wor…
Energy management is a critical aspect of risk assessment for Uncrewed Aerial Vehicle (UAV) flights, as a depleted battery during a flight brings almost guaranteed vehicle damage and a high risk of human injuries or property damage. Predicting the amount of energy a flight will consume is challenging as routing, weather, obstacles, and other factors affect the overall consumption. We develop a deep energy model for a UAV that uses Temporal Convolutional Networks to capture the time varying features while incorporating static contextual information. Our energy model is trained on a real world d…
Energy sources such as batteries do not decrease in mass after consumption, unlike combustion-based fuels. We present the concept of staging energy sources, i.e. consuming energy in stages and ejecting used stages, to progressively reduce the mass of aerial vehicles in-flight which reduces power consumption, and consequently increases flight time. A flight time vs. energy storage mass analysis is presented to show the endurance benefit of staging to multirotors. We consider two specific problems in discrete staging -- optimal order of staging given a certain number of energy sources, and optim…
In this paper a vision-based system for detection, motion tracking and following of Unmanned Aerial Vehicle (UAV) with other UAV (follower) is presented. For detection of an airborne UAV we apply a convolutional neural network YOLO trained on a collected and processed dataset of 10,000 images. The trained network is capable of detecting various multirotor UAVs in indoor, outdoor and simulation environments. Furthermore, detection results are improved with Kalman filter which ensures steady and reliable information about position and velocity of a target UAV. Preserving the target UAV in the fi…
Recently, needs for unmanned aerial vehicles (UAVs) that are attachable to the wall have been highlighted. As one of the ways to address the need, researches on various tilting multirotors that can increase maneuverability has been employed. Unfortunately, existing studies on the tilting multirotors require considerable amounts of prior information on the complex dynamic model. Meanwhile, reinforcement learning on quadrotors has been studied to mitigate this issue. Yet, these are only been applied to standard quadrotors, whose systems are less complex than those of tilting multirotors. In this…
Beijing Institute for General Artificial Intelligence（北京通用人工智能研究院）；Tsinghua University（清华大学）；Peking University（北京大学）
Tracking position and orientation independently affords more agile maneuver for over-actuated multirotor Unmanned Aerial Vehicles (UAVs) while introducing undesired downwash effects; downwash flows generated by thrust generators may counteract others due to close proximity, which significantly threatens the stability of the platform. The complexity of modeling aerodynamic airflow challenges control algorithms from properly compensating for such a side effect. Leveraging the input redundancies in over-actuated UAVs, we tackle this issue with a novel control allocation framework that considers d…
This paper presents PANTHER, a real-time perception-aware (PA) trajectory planner for multirotor-UAVs (Unmanned Aerial Vehicles) in dynamic environments. PANTHER plans trajectories that avoid dynamic obstacles while also keeping them in the sensor field of view (FOV) and minimizing the blur to aid in object tracking. The rotation and translation of the UAV are jointly optimized, which allows PANTHER to fully exploit the differential flatness of multirotors to maximize the PA objective. Real-time performance is achieved by implicitly imposing the underactuated dynamics of the UAV through the Ho…
King Abdullah University of Science & Technology（阿卜杜拉国王科技大学）；University of Maryland（马里兰大学）；Polytechnique Montreal（蒙特利尔理工学院）；Australian College of Kuwait（科威特澳大利亚学院）
We present the Robotics Intelligent Systems & Control (RISC) Lab multiagent testbed for reliable search and rescue and aerial transport in outdoor environments. The system consists of a team of three multirotor unmanned aerial vehicles (UAVs), which are capable of autonomously searching, picking up, and transporting randomly distributed objects in an outdoor field. The method involves vision based object detection and localization, passive aerial grasping with our novel design, GPS based UAV navigation, and safe release of the objects at the drop zone. Our cooperative strategy ensures safe spa…
Multi-Domain Physics-Based MDO of Multirotor UAVs: A Deterministic Framework for Discrete COTS Sizing
International Institute of Information Technology, Hyderabad（印度海得拉巴国际信息技术学院）；Indian Institute of Science Education and Research, Bhopal（印度博帕尔科学教育与研究学院）
Localization is one of the most important technologies needed to use Unmanned Aerial Vehicles (UAVs) in actual fields. Currently, most UAVs use GNSS to estimate their position. Recently, there have been attacks that target the weaknesses of UAVs that use GNSS, such as interrupting GNSS signal to crash the UAVs or sending fake GNSS signals to hijack the UAVs. To avoid this kind of situation, this paper proposes an algorithm that deals with the localization problem of the UAV in GNSS-denied environments. We propose a localization method, named as BRM (Building Ratio Map based) localization, for …
This paper aims to develop a Fault Tolerant Control (FTC) architecture, for the case of a damaged actuator for a multirotor UAV that can be applied across multirotor platforms based on their Attainable Virtual Control Set (AVCS). The research is aimed to study the AVCS and identify the parameters that limit the controllability of multirotor UAV post an actuator failure. Based on the study of controllability, the requirements for a FTC is laid out. The implemented control solution will be tested on a quadrotor, Intel Shooting Star UAV platform in indoor and outdoor flights using only the onboar…
Robotics Institute, Carnegie Mellon University（卡内基梅隆大学机器人研究所）；University of Pittsburgh（匹兹堡大学）
The introduction of fully-actuated multirotors has opened the door to new possibilities and more efficient solutions to many real-world applications. However, their integration had been slower than expected, partly due to the need for new tools to take full advantage of these robots. As far as we know, all the groups currently working on the fully-actuated multirotors develop new full-pose (6-D) tools and methods to use their robots, which is inefficient, time-consuming, and requires many resources. We propose a way of bridging the gap between the tools already available for underactuated robo…
We present a waypoint planning algorithm for an unmanned aerial vehicle (UAV) that is teamed with an unmanned ground vehicle (UGV) for the task of search and rescue in a subterranean environment. The UAV and UGV are teamed such that the localization of the UAV is conducted on the UGV via the multi-sensor fusion of a fish-eye camera, 3D LIDAR, ranging radio, and a laser altimeter. Likewise, the trajectory planning of the UAV is conducted on the UGV, which is assumed to have a 3D map of the environment (e.g., from Simultaneous Localization and Mapping). The goal of the planning algorithm is to s…
Unmanned aerial vehicles (UAVs) are becoming largely ubiquitous with an increasing demand for aerial data. Accurate navigation and localization, required for precise data collection in many industrial applications, often relies on RTK GNSS. These systems, able of centimeter-level accuracy, require a setup and calibration process and are relatively expensive. This paper addresses the problem of accurate positioning and navigation of UAVs through cooperative localization. Inexpensive ultra-wideband (UWB) transceivers installed on both the UAV and a support ground robot enable centimeter-level re…
Considering the accelerated development of Unmanned Aerial Vehicles (UAVs) applications in both industrial and research scenarios, there is an increasing need for localizing these aerial systems in non-urban environments, using GNSS-Free, vision-based methods. Our paper proposes a vision-based localization algorithm that utilizes deep features to compute geographical coordinates of a UAV flying in the wild. The method is based on matching salient features of RGB photographs captured by the drone camera and sections of a pre-built map consisting of georeferenced open-source satellite images. Ex…
Faculty of Electrical Engineering, Czech Technical University in Prague（捷克技术大学电气工程学院）
Autonomous operation of UAVs in a closed environment requires precise and reliable pose estimate that can stabilize the UAV without using external localization systems such as GNSS. In this work, we are concerned with estimating the pose from laser scans generated by an inexpensive and lightweight LIDAR. We propose a localization system for lightweight (under 200g) LIDAR sensors with high reliability in arbitrary environments, where other methods fail. The general nature of the proposed method allows deployment in wide array of applications. Moreover, seamless transitioning between different k…
Tag-based visual-inertial localization is a lightweight method for enabling autonomous data collection missions of low-cost unmanned aerial vehicles (UAVs) in indoor construction environments. However, finding the optimal tag configuration (i.e., number, size, and location) on dynamic construction sites remains challenging. This paper proposes a perception-aware genetic algorithm-based tag placement planner (PGA-TaPP) to determine the optimal tag configuration using 4D-BIM, considering the project progress, safety requirements, and UAV's localizability. The proposed method provides a 4D plan f…
JointLoc: A Real-time Visual Localization Framework for Planetary UAVs Based on Joint Relative and Absolute Pose Estimation
School of Aeronautics and Astronautics, University of Chinese Academy of Sciences（中国科学院大学航空宇航学院）；Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences（中国科学院空间应用工程与技术中心）；School of Artificial Intelligence, Jilin University（吉林大学人工智能学院）
Fusion of Visual-Inertial Odometry with LiDAR Relative Localization for Cooperative Guidance of a Micro-Scale Aerial Vehicle
Multi-robot Systems Group, Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Technick\'a 2, Prague, 166 27, Czech Republic
Fly, Track, Land: Infrastructure-less Magnetic Localization for Heterogeneous UAV-UGV Teaming
Department of Engineering, University of Perugia（工程系，佩鲁吉亚大学）；Multi-Robot Systems Group, Faculty of Electrical Engineering, Czech Technical University in Prague（多机器人系统组，电气工程系，布拉格捷克技术大学）；D-ITET Department, ETH Zürich（D-ITET部门，苏黎世联邦理工学院）
Droneulator: A Portable UAV Simulator for Agricultural Workflows with RotorPy and Godot 4
Lincoln Centre for Autonomous Systems (L-CAS), University of Lincoln, Lincoln, UK（林肯自主系统中心（L-CAS）、林肯大学、林肯，英国）；Faculty of Aerospace Engineering, MAVLab, Delft University of Technology (TU Delft), Delft, Netherlands（航空航天工程学院、MAVLab、代尔夫特理工大学（TU Delft）、代尔夫特，荷兰）
Neural-Geometric Tunnel Traversal: Localization-free UAV Flight with Tilted LiDARs
Centro Universitario de la Defensa, Zaragoza（萨拉戈萨国防大学中心）；Instituto de Investigación en Ingeniería de Aragón（阿拉贡工程研究院）；University of Zaragoza（萨拉戈萨大学）；Investigación en Ingeniería de Aragón（阿拉贡工程研究院）
Reflection-Based Relative Localization for Cooperative UAV Teams Using Active Markers
Multi-Robot Systems Group, Faculty of Electrical Engineering, Czech Technical University in Prague（布拉格捷克技术大学电气工程系多机器人系统组）；Mohammed VI Polytechnic University（摩洛哥穆莱伊沙·穆莱·阿卜杜勒阿齐兹·本·阿卜杜勒阿齐兹·本·阿卜杜勒·阿齐兹·本·阿卜杜勒·阿齐兹·本·阿卜杜勒·阿齐兹·本·阿卜杜勒·阿齐兹·本·阿卜杜勒·阿齐兹·本·阿卜杜勒·阿齐兹·本·阿卜杜勒·阿齐兹·本·阿卜杜勒·阿齐-middle Polytechnic University）
The field of Unmanned Aerial Vehicles (UAVs) has reached a high level of maturity in the last few years. Hence, bringing such platforms from closed labs, to day-to-day interactions with humans is important for commercialization of UAVs. One particular human-UAV scenario of interest for this paper is the payload handover scheme, where a UAV hands over a payload to a human upon their request. In this scope, this paper presents a novel real-time human-UAV interaction detection approach, where Long short-term memory (LSTM) based neural network is developed to detect state profiles resulting from h…
University of Toronto Institute for Aerospace Studies（多伦多大学航空航天研究所）
We propose and demonstrate a fast, robust method for using satellite images to localize an Unmanned Aerial Vehicle (UAV). Previous work using satellite images has large storage and computation costs and is unable to run in real time. In this work, we collect Google Earth (GE) images for a desired flight path offline and an autoencoder is trained to compress these images to a low-dimensional vector representation while retaining the key features. This trained autoencoder is used to compress a real UAV image, which is then compared to the precollected, nearby, autoencoded GE images using an inne…
