69 accepted papers
Aerial transportation using quadrotors with cable-suspended payloads holds great potential for applications in disaster response, logistics, and infrastructure maintenance. However, their hybrid and underactuated dynamics pose significant control and perception challenges. Traditional approaches oft
Aerial transportation using quadrotors with cable-suspended payloads holds great potential for applications in disaster response, logistics, and infrastructure maintenance. However, their hybrid and underactuated dynamics pose significant control and perception challenges. Traditional approaches oft…
The multi-robot unlabeled motion planning problem of concurrently assigning robots to goals and generating safe trajectories is central in many collaborative tasks. Recent Graph Neural Network methods offer scalable decentralized solutions but rely on simplified dynamics and simulation environments,…
Search and rescue operations require unmanned aerial vehicles to both traverse unknown unstructured environments at high speed and track targets once detected. Achieving both capabilities under degraded sensing and without global localization remains an open challenge. Recent works on relative navig…
The increasing use of drones in human-centric applications highlights the need for designs that can survive collisions and recover rapidly, minimizing risks to both humans and the environment. We present HoLoArm, a quadrotor with compliant arms inspired by the nodus structure of dragonfly wings. Thi…
Autonomous aerial target tracking in unstructured and GPS-denied environments remains a fundamental challenge in robotics. Many existing methods rely on motion capture systems, pre-mapped scenes, or feature-based localization to ensure safety and control, limiting their deployment in real-world cond…
Deploying learned multi-robot models on heterogeneous robots remains challenging due to hardware heterogeneity, communication constraints, and the lack of a unified execution stack. This paper presents NeuroMesh, a multi-domain, cross-platform, and modular decentralized neural inference framework th
Aerial transportation robots using suspended cables have emerged as versatile platforms for disaster response and rescue operations. To maximize the capabilities of these systems, robots need to aggressively fly through tightly constrained environments, such as dense forests and structurally unsafe
Aerial transportation robots using suspended cables have emerged as versatile platforms for disaster response and rescue operations. To maximize the capabilities of these systems, robots need to aggressively fly through tightly constrained environments, such as dense forests and structurally unsafe …
Deep learning methods for Visual Place Recognition (VPR) have advanced significantly, largely driven by large-scale datasets. However, most existing approaches are trained on a single dataset, which can introduce dataset-specific inductive biases and limit model generalization. While multi-dataset j…
Gliding offers small fixed-wing UAVs extended endurance and silent operation but requires accurate energy management, especially under wind disturbances and obstacle constraints. Traditional Total Energy Control Systems based controllers regulate the trade between potential and kinetic energy reacti…
Multi-quadrotor systems face significant challenges in decentralized control, particularly with safety and coordination under sensing and communication limitations. State-of-the-art methods leverage Control Barrier Functions (CBFs) to provide safety guarantees but often neglect actuation constraints
Quadrotors equipped with cable-suspended loads represent a versatile, low-cost, and energy efficient solution for aerial transportation, construction, and manipulation tasks. However, their real-world deployment is hindered by several challenges. The system is difficult to control because it is nonl
In this paper, we present a novel trajectory planning algorithm for cooperative manipulation with multiple quadrotors using control barrier functions (CBFs). Our approach addresses the complex dynamics of a system in which a team of quadrotors transports and manipulates a cable-suspended rigid-body
Reactive collision avoidance is essential for agile robots navigating complex and dynamic environments, enabling real-time obstacle response. However, this task is inherently challenging because it requires a tight integration of perception, planning, and control, which traditional methods often han
Paired RGB-thermal data is crucial for visual-thermal sensor fusion and cross-modality tasks, including important applications such as multi-modal image alignment and retrieval. However, the scarcity of synchronized and calibrated RGB-thermal image pairs presents a major obstacle to progress in thes…
Efficient real-time trajectory planning and control for fixed-wing unmanned aerial vehicles is challenging due to their non-holonomic nature, complex dynamics, and the additional uncertainties introduced by unknown aerodynamic effects. In this paper, we present a fast and efficient real-time traject
Geo-localization is an essential component of Unmanned Aerial Vehicle (UAV) navigation systems to ensure precise absolute self-localization in outdoor environments. To address the challenges of GPS signal interruptions or low illumination, Thermal Geo-localization (TG) employs aerial thermal imagery
In the past decade, although single-robot perception has made significant advancements, the exploration of multi-robot collaborative perception remains largely unexplored. This involves fusing compressed, intermittent, limited, heterogeneous, and asynchronous environmental information across multipl
Recently non-linear control methods like Model Predictive Control (MPC) and Reinforcement Learning (RL) have attracted increased interest in the quadrotor control community. In contrast to classic control methods like cascaded PID controllers, MPC and RL heavily rely on an accurate model of the syst…
Aerial robots are required to remain operational even in the event of system disturbances, damages, or failures to ensure resilient and robust task completion and safety. One common failure case is propeller damage, which presents a significant challenge in both quantification and compensation. In t
The problem of assigning a set of spatial goals to a team of robots plays a crucial role in various multi-robot planning applications including, but not limited to exploration, search and rescue, or surveillance. The Linear Sum Assignment Problem (LSAP) is a common way of formulating and resolving t
Accurate modeling of system dynamics is crucial for achieving high-performance planning and control of robotic systems. Although existing data-driven approaches represent a promising approach for modeling dynamics, their accuracy is limited to a short prediction horizon, overlooking the impact of co…
Learning-based methods, particularly Reinforcement Learning (RL), hold great promise for streamlining deployment, enhancing performance, and achieving generalization in the control of autonomous multirotor aerial vehicles. Deep RL has been able to control complex systems with impressive fidelity and
In this letter, we propose a new approach for human motion reconstruction based on Gaussian Mixture Probability Hypothesis Density (GM-PHD) Filter applied to human joint positions extracted from RGB-D camera (e.g. Kinect). Existing inference approaches require a proper association between measuremen
Accurate geo-localization of Unmanned Aerial Vehicles (UAVs) is crucial for outdoor applications including search and rescue operations, power line inspections, and environmental monitoring. The vulnerability of Global Navigation Satellite Systems (GNSS) signals to interference and spoofing necessit
Aerial robots have the potential to play a crucial role in assisting humans with complex and dangerous tasks. Nevertheless, the future industry demands innovative solutions to streamline the interaction process between humans and drones to enable seamless collaboration and efficient coworking. In th…
In the last decade, data-driven approaches have become popular choices for quadrotor control, thanks to their ability to facilitate the adaptation to unknown or uncertain flight conditions. Among the different data-driven paradigms, Deep Reinforcement Learning (DRL) is currently one of the most expl…
Visual control enables quadrotors to adaptively navigate using real-time sensory data, bridging perception with action. Yet, challenges persist, including generalization across scenarios, maintaining reliability, and ensuring real-time responsiveness. This paper introduces a perception framework gro…
Battery endurance represents a key challenge for long-term autonomy and long-range operations, especially in the case of aerial robots. In this paper, we propose AutoCharge, an autonomous charging solution for quadrotors that combines a portable ground station with a flexible, lightweight charging t…
Gaussian Processes (GPs) are expressive models for capturing signal statistics and expressing prediction uncer-tainty. As a result, the robotics community has gathered interest in leveraging these methods for inference, planning, and control. Unfortunately, despite providing a closed-form inference…
The ability of aerial robots to operate in the presence of failures is crucial in various applications that demand continuous operations, such as surveillance, monitoring, and inspection. In this paper, we propose a fault-tolerant control strategy for quadrotors that can adapt to single and dual com…
Onboard sensors, such as cameras and thermal sensors, have emerged as effective alternatives to Global Positioning System (GPS) for geo-Iocalization in Unmanned Aerial Vehicle (UAV) navigation. Since GPS can suffer from signal loss and spoofing problems, researchers have explored camera-based techni…
Autonomous Micro Aerial Vehicles (MAVs) such as quadrotors equipped with manipulation mechanisms have the potential to assist humans in tasks such as construction and package delivery. Cables are a promising option for manipulation mechanisms due to their low weight, low cost, and simple design. How…
Autonomous exploration is a longstanding goal of the robotics community. Aerial drone navigation has proven to be especially challenging. The stringent requirements on cost, weight, maneuverability, and power consumption do not allow exploration approaches to easily be employed or adapted to differe
Aerial robots can enhance their safe and agile navigation in complex and cluttered environments by efficiently exploiting the information collected during a given task. In this paper, we address the learning model predictive control problem for quadrotors. We design a learning receding-horizon nonli…
Multi-robot systems such as swarms of aerial robots are naturally suited to offer additional flexibility, resilience, and robustness in several tasks compared to a single robot by enabling cooperation among the agents. To enhance the autonomous robot decision-making process and situational awareness
Accurately modeling quadrotor's system dynamics is critical for guaranteeing agile, safe, and stable navigation. The model needs to capture the system behavior in multiple flight regimes and operating conditions, including those producing highly nonlinear effects such as aerodynamic forces and torqu
In this paper, we address the vision-based detection and tracking problems of multiple aerial vehicles using a single camera and Inertial Measurement Unit (IMU) as well as the corresponding perception consensus problem (i.e., uniqueness and identical IDs across all observing agents). We design sever…
Autonomous Micro Aerial Vehicles (MAVs) have the potential to be employed for surveillance and monitoring tasks. By perching and staring on one or multiple locations aerial robots can save energy while concurrently increasing their overall mission time without actively flying. In this paper, we addr…
Micro Aerial Vehicles (MAVs) have the great potential to be deployed in commercial or health care services such as e-commerce package delivery, transportation of medicines, same-day food delivery, and other time-sensitive transportation tasks. A team of MAVs can cooperatively transport objects to ov
Mobile manipulators have the potential to revolutionize modern agriculture, logistics and manufacturing. In this work, we present the design of a ground-based mobile manipulator for automated structure assembly. The proposed system is capable of autonomous localization, grasping, transportation and
In this paper, we address the Perception– Constrained Model Predictive Control (PCMPC) and state estimation problems for quadrotors with cable suspended payloads using a single camera and Inertial Measurement Unit (IMU). We design a receding–horizon control strategy for cable suspended payloads dire…
We address the detection, tracking, and relative localization of the agents of a drone swarm from a human perspective using a headset equipped with a single camera and an Inertial Measurement Unit (IMU). We train and deploy a deep neural network detector on image data to detect the drones. A joint p
Estimating the 6D pose of objects is beneficial for robotics tasks such as transportation, autonomous navigation, manipulation as well as in scenarios beyond robotics like virtual and augmented reality. With respect to single image pose estimation, pose tracking takes into account the temporal infor…
Quadrotor flight in cluttered, unknown environments is challenging due to the limited range of perception sensors, challenging obstacles, and limited onboard computation. In this work, we directly address these challenges by proposing an efficient, reactive planning approach. We introduce the Bitwis…
Robots are ideally suited to performing simple tasks in dangerous environments. In this letter, we address the use of robots for inspection of nuclear reactors which may be contaminated by radiation. The geometry of a reactor vessel is three-dimensional with significant clutter. Accordingly, we prop
In this letter, we demonstrate that a quadrotor's tilt, angular velocity, linear velocity and the parameters shown in Table II may be estimated using only an inertial measurement unit (IMU) and motor speed feedback for sensing. Motor speed commands are used to drive the process model and the motor s
In this letter, we address the problem of providing human-assisted quadrotor navigation using a set of eye tracking glasses. The advent of these devices (i.e., eye tracking glasses, virtual reality tools, etc.) provides the opportunity to create new, noninvasive forms of interaction between humans a
This letter addresses the velocity and attitude estimation of a quadrotor using motor speeds and inertial measurement unit (IMU) data. This result is obtained through a novel filter that employs a first-order drag model, which allows the velocity to be observed through the drag forces acting on the
Real-time semantic image segmentation on platforms subject to size, weight, and power constraints is a key area of interest for air surveillance and inspection. In this letter, we propose MAVNet: a small, light-weight, deep neural network for real-time semantic segmentation on micro aerial vehicles
Accurate knowledge of geometric and inertia parameters are a necessity for precise and robust control of aerial vehicles. We propose a novel filter that is able to fuse motor speed, inertia, and pose measurements to estimate the vehicle's key dynamic properties online. The presented framework is abl…
Micro aerial vehicles have the potential to assist humans in tasks such as manipulation and transportation for construction and humanitarian missions, beyond simply acquiring data and building maps. In this letter, we address the state estimation, control, and trajectory planning in cooperative tran
This work addresses the design and implementation of a filter that estimates the orientation of the body-fixed z axis and the velocity of a quadrotor UAV from the inertial measurement unit (IMU) given a known yaw. The velocity and attitude estimation is possible since the filter employs a linear dra…
Autonomous Micro Aerial Vehicles (MAVs) have the potential to assist in real-life tasks involving grasping and transportation, but not before solving several difficult research challenges. In this work, we address the design, control, estimation, and planning problems for cooperative localization, g
We propose a novel approach for optimal trajectory tracking for unmanned aerial vehicles (UAV), using a linear model predictive controller (MPC) in combination with non-linear state feedback. The solution relies on fast onboard simulation of the translational dynamics of the UAV, which is guided by…
Micro Aerial Vehicles have the potential to assist humans in real life tasks involving applications such as smart homes, search and rescue, and architecture construction. To enhance autonomous navigation capabilities these vehicles need to be able to create dense 3D maps of the environment, while co…
In this letter, we consider state estimation and local mapping with a micro aerial vehicle inside a tunnel that can be modeled as a generalized cylinder, using a three-dimensional lidar and an inertial measurement unit. This axisymmetric environment poses unique challenges in terms of localization a
In this letter, we present the system infrastructure for a swarm of quadrotors, which perform all estimation on board using monocular visual inertial odometry. This is a novel system since it does not require an external motion capture system or GPS and is able to execute formation tasks without int
In this letter, we address the autonomous flight of a small quadrotor, enabling tracking of a moving object. The 15-cm diameter, 250-g robot relies only on onboard sensors (a single camera and an inertial measurement unit) and computers, and can detect, localize, and track moving objects. Our key co
In this paper, we address the estimation, control, navigation and mapping problems to achieve autonomous inspection of penstocks and tunnels using aerial vehicles with on-board sensing and computation. Penstocks and tunnels have the shape of a generalized cylinder. They are generally dark and featur
We address the state estimation, control, and planning for aggressive flight with a 150 cm diameter, 250 g quadrotor equipped only with a single camera and an inertial measurement unit (IMU). The use of smartphone grade hardware and the small scale provides an inexpensive and practical solution for
In the last decade, consumer electronic devices such as smartphones, are packaged with small cameras, gyroscopes, and accelerometers, all sensors allowing autonomous deployment of aerial robots in GPS-denied environments. Our previous work [1], demonstrated the feasibility of using smartphones for a…
This letter addresses vision-based localization and servoing for quadrotors to enable autonomous perching by hanging from cylindrical structures using only a monocular camera. We focus on the problems of relative pose estimation, control, and trajectory planning for maneuvering a robot relative to c
The combination of on-board sensors measurements with different statistical characteristics can be employed in robotics for localization and control, especially in GPS-denied environments. In particular, most aerial vehicles are packaged with low cost sensors, important for aerial robotics, such as
The so-called direct visual SLAM methods have shown a great potential in estimating a semidense or fully dense reconstruction of the scene, in contrast to the sparse reconstructions of the traditional feature-based algorithms. In this paper, we propose for the first time a direct, tightly-coupled fo
The fusion of IMU and RGB-D sensors presents an interesting combination of information to achieve autonomous localization and mapping using robotic platforms such as ground robots and flying vehicles. In this paper, we present a software framework for cooperative localization and mapping while simul…
Consumer grade technology seen in cameras and phones has led to the price/performance ratio of sensors and processors falling dramatically over the last decade. In particular, most devices are packaged with a camera, a gyroscope, and an accelerometer, important sensors for aerial robotics. The low m…