Aerial Robots Research Articles

Aerial Physical Human Robot Interaction for Payload Transportation

Aerial Physical Human Robot Interaction for Payload Transportation

A Multirobot System for 3-D Surface Reconstruction With Centralized and Distributed Architectures

In this article, we propose an original solution to the problem of surface reconstruction of large-scale unknown environments, with multiple cooperative robots. As they progress through the 3-D environment, the robots rely on volumetric maps obtained via a TSDF representation to extract discrete incomplete surface elements (ISEs), and a list of candidate viewpoints is generated to cover them. A next-best-view planning approach, which approximately solves a traveling salesman problem (TSP) via greedy allocation, is then used to iteratively assign these viewpoints to the robots. Two multiagent architectures, a centralized one (TSP-Greedy Allocation or TSGA) and a distributed one (dist-TSGA), in which the robots locally compute their maps and share them, are developed and compared. Extensive numerical and real-world experiments with multiple aerial and ground robots in challenging 3-D environments show the flexibility and effectiveness of our surface representation of a volumetric map. The experiments also shed light on the nexus between reconstruction accuracy and surface completeness, and between total distance traveled and execution time.

RETRACTED ARTICLE: Alternating-direction-method-of-multipliers-based fast model predictive control for an aerial trees-pruning robot

RETRACTED ARTICLE: Alternating-direction-method-of-multipliers-based fast model predictive control for an aerial trees-pruning robot

Relative Transformation Estimation Based on Fusion of Odometry and UWB Ranging Data

In this article, we study the problem of estimating the four-degree-of-freedom (3-D position and heading) robot-to-robot relative frame transformation using onboard odometry and interrobot distance measurements. First, we present a theoretical analysis of the problem, namely, the derivation and interpretation of the Cramèr–Rao lower bound, the Fisher information matrix, and its determinant. Second, we propose optimization-based solutions, including a quadratically constrained quadratic programming (QCQP) formulation and its semidefinite programming (SDP) relaxation. Third, based on the theoretical results, we can detect singular configurations as well as measure the uncertainty of each individual parameter. We perform extensive simulations and real-life experiments with aerial robots to show that the proposed QCQP and SDP methods can outperform state-of-the-art approaches, especially in geometrically poor or large measurement noise conditions. In general, the QCQP method provides the best results at the expense of computational time, while the SDP method runs much faster and is sufficiently accurate in most cases.

Fast terminal synergetic control for morphing quadcopter with time-varying parameters

To enhance flexibility and improve versatility, recent research has focused on the development of variable structure vehicles. In line with this, this paper introduces a morphing quadcopter with time-varying parameters that enables independent rotation of its arms around the main body. This study highlights the influence of these parameters on the geometric properties, dynamics, flight stability, and control of this aerial robot, while considering nonlinear functions, unknown parameters, and external disturbances. The system dynamics are derived using Newton-Euler formalism, and a robust control approach based on synergetic theory is proposed. The distinctive features of this strategy are demonstrated through finite-time convergence, enhanced control accuracy, and effective chattering suppression. In the control aspect, a Synergetic Controller (SC) is initially developed and further improved by incorporating fast finite-time convergence of the state variables. A comparative study is conducted, quantitatively and qualitatively, among four controllers: BackStepping (BS) controller, Sliding Mode Controller (SMC), SC, and Fast Terminal Synergetic Controller (FTSC). The FTSC exhibits numerous advantages, including rapid tracking towards desired states, adaptability to varying system parameters and uncertain external disturbances, as well as suitability for digital implementation. To conduct a significant comparative study, a Genetic Algorithm is employed to select the optimal gains for each control technique. Additionally, to imitate the real situation as much as possible, external disturbances are considered in the performed numerical simulation. Overall, the results demonstrate that the proposed control technique outperforms in terms of accuracy and robustness. It offers superior control performance and effective handling of system variations and external disturbances, making it a promising approach for the morphing quadcopter system.

Aerial Manipulation via Modular Quadrotors With Passively Foldable Airframes

The need for physical interactions and aerial manipulation has driven the demand for small multirotor vehicles with higher degrees of actuation and adaptability. This leads to the development of reconfigurable flying robots and modular flight platforms. In this work, we propose a modular vehicle comprising flight-capable quadrotors with passively deformable rotor arms as subunits. The foldable arms with preloaded elastic components are designed to be stable in both folded and unfolded states such that the reconfiguration can be achieved passively through the manipulation of the propelling thrust. A docking mechanism is devised to permit multiple modules to combine during a mission without human intervention. Through a series of experiments, we show that passive reconfigurability enables the platform to perform perching. With the added modularity, the integrated platform can be used to perform thrust vectoring or grip and transport heavier payloads. The ability to accomplish a wide range of tasks in a single platform is unique from existing aerial robots, thanks to the combination of reconfigurability and modularity.

Contact-Prioritized Planning of Impact-Resilient Aerial Robots With an Integrated Compliant Arm

Contact-Prioritized Planning of Impact-Resilient Aerial Robots With an Integrated Compliant Arm

Autonomous aerial robotics for package delivery: A technical review

AbstractSmall unmanned aerial vehicles (UAVs) have gained significant interest in the last decade. More specifically these vehicles have the capacity to impact package delivery logistics in a disruptive way. This paper reviews research problems and state‐of‐the‐art solutions that facilitate package delivery. Different aerial manipulators and grippers are listed along with control techniques to address stability issues. Landing on a platform is next discussed which encompasses static and dynamic platforms. Landing on a dynamic platform presents further challenges. This includes delayed control responses and poor precision of the relative motion between the platform and the aerial vehicle. Subsequently, risks such as weather conditions, state estimation, and collision avoidance to ensure safe transit is considered. Finally, delivery UAV routing is investigated which categorizes the topic into two areas: drone operations and drone–truck collaborative operations. Additionally, we compare the solutions against design, environmental, and legal constraints.

The single robot line coverage problem: Theory, algorithms, and experiments

AbstractLine coverage is the task of servicing a given set of one‐dimensional features in an environment. It is important for the inspection of linear infrastructure such as road networks, power lines, and oil and gas pipelines. This paper addresses the single robot line coverage problem for aerial and ground robots by modeling it as an optimization problem on a graph. The problem belongs to the broad class of arc routing problems and is closely related to the rural postman problem (RPP) on asymmetric graphs. The paper presents an integer linear programming formulation with proofs of correctness. Using the minimum cost flow problem, we develop approximation algorithms with guarantees on the solution quality. These guarantees also improve the existing results for the asymmetric RPP. The main algorithm partitions the problem into three cases based on the structure of the required graph, that is, the graph induced by the features that require servicing. We evaluate our algorithms on road networks from the 50 most populous cities in the world, consisting of up to 730 road segments. The algorithms, augmented with improvement heuristics, run within 3 s and generate solutions that are within 10% of the optimum. We experimentally demonstrate our algorithms with commercial UAVs on the UNC Charlotte campus road network.

Design, Control, and Motion Strategy of TRADY: Tilted‐Rotor‐Equipped Aerial Robot With Autonomous In‐Flight Assembly and Disassembly Ability

State‐of‐the‐art aerial robots often prioritize maneuverability or manipulation capabilities, making it difficult to achieve both. The issue arises because aerial robots with agile mobility lack sufficient rotors for manipulation tasks, while those with manipulation ability are too large for agile mobility. To tackle this problem, a novel aerial robot unit named TRADY, tilted‐rotor‐equipped aerial robot with autonomous in‐flight assembly and disassembly capability, is introduced. The TRADY unit can self‐assemble/disassemble with another unit in mid‐air, adjusting the aircraft's control freedom by switching between under‐actuated and fully‐actuated control models. The system implementation involves a docking mechanism design, optimized rotor configuration, as well as a control system with the ability to switch between under‐actuated and fully‐actuated controllers. A proposed state transition method compensates for discrete changes during the controller switchover process. Also, a motion strategy for assembly/disassembly with hazardous condition recovery behavior is presented. Finally, through experiments, TRADY demonstrated a 90 % success rate in executing assembly/disassembly motions, and in the assembly state, it can utilize full‐pose tracking and generate over nine times the torque of a single unit. This is the first aerial robot developed to perform both assembly and disassembly while seamlessly transitioning between fully‐actuated and under‐actuated models.

Urban Firefighting Drones: Precise Throwing from UAV

In recent years, the use of unmanned aerial vehicles has spread across different fields of the industry due to their ease of deployment and minimal operational risk. Firefighting is a dangerous task for the humans involved, in which the use of UAVs presents itself as a good first-action protocol for a rapid response to an incipient fire because of their safety and speed of action. Current research is mainly focused on wildland fires, but fires in urban environments are barely mentioned in the bibliography. To motivate the research on this topic, ICUAS’22 organized an international competition inspired by this mission, with the challenge of a UAV traversing an area populated by obstacles, finding a target, and precisely throwing a ball to it. For this competition, the Computer Vision and Aerial Robotics (CVAR-UPM) team developed a solution composed of multiple modules and structured by a mission planner. In this paper, we describe our approach and the developed architecture that led us to be awarded the first prize in the competition.

Adaptive neural network based compensation control of quadrotor for robust trajectory tracking

SummaryNeural network (NN) methods have become increasingly efficient and applicable in control. This article presents a novel nested control strategy based on adaptive radial basis function neural networks (RBFNN) and NN supervised control embedded with integrator back stepping (IBS) for a robust position and attitude trajectory tracking of quadrotor aerial robot in presence of modeling uncertainties, sensing noise, and external bounded disturbance. The control philosophy is derived from the decentralized inverse dynamics, where the adaptive RBFNN is adopted for the outer loop to approximate the unknown external disturbance, and adaptively compensate for their effect. In conjunction with a supervised control that stabilizes the attitude in the inner loop by adaptively compensating the unknown and unmodeled uncertainties, avoiding initial instability of the attitude during NN convergence. Furthermore, noise is attenuated by an adaptive extended Kalman filter. Stability analysis was elaborated using Lyapunov stability theory. Simulation of adaptive RBFNN control philosophy proved robustness and effectiveness compared to proportional integral derivative, IBS, and offline decentralized convolution neural network algorithms as it generates the control law by guarantying a fast convergence of parameters, better external disturbance compensation, and noise attenuation. The proposed scheme of robust tracking was validated.

A Self-Rotary Aerial Robot With Passive Compliant Variable-Pitch Wings

Inspired by maple seeds, the self-rotary winged aerial robots reflect the advantages of both multi-rotor aircraft and fixed-wing robots. However, their self-rotating speed is related to the takeoff weight, which may affect their application and flight stabilization. To provide a practical and feasible solution, this work proposes a passive compliant variable-pitch mechanism on the self-rotary winged aircraft without requiring extra actuators. Depending on the weight of the payload, the pitching angle of the wings can be passively varied to minimize the increase in the rotating speed and enhance attitude stabilization ability. Besides, an adaptive attitude controller is also designed to address the challenges in attitude stabilization, which are caused by parameter uncertainties and the variable pitching angle. To elaborate on the design and fabrication of the prototype, necessary identification experiments are arranged to find the relationship of pitching angle, thrust generation, power draw, and rotating speed. The experimental findings indicate the proposed robot with optimal pitch angles achieves around 56.8% more power loading than using propellers directly, from 4.4 to 6.9 g/w. The combination of the passive compliant mechanism and adaptive controller improves flight performance from 0.16 to 0.08 meters (mean of absolute translational error).

Learning to Navigate in Turbulent Flows With Aerial Robot Swarms: A Cooperative Deep Reinforcement Learning Approach

Aerial operation in turbulent environments is a challenging problem due to the chaotic behavior of the flow. This problem is made even more complex when a team of aerial robots is trying to achieve coordinated motion in turbulent wind conditions. In this paper, we present a novel multi-robot controller to navigate in turbulent flows, decoupling the trajectory-tracking control from the turbulence compensation via a nested control architecture. Unlike previous works, our method does not learn to compensate for the air-flow at a specific time and space. Instead, our method learns to compensate for the flow based on its effect on the team. This is made possible via a deep reinforcement learning approach, implemented via a Graph Convolutional Neural Network (GCNN)-based architecture, which enables robots to achieve better wind compensation by processing the spatial-temporal correlation of wind flows across the team. Our approach scales well to large robot teams -- as each robot only uses information from its nearest neighbors -- , and generalizes well to robot teams larger than seen in training. Simulated experiments demonstrate how information sharing improves turbulence compensation in a team of aerial robots and demonstrate the flexibility of our method over different team configurations.

Exocentric control scheme for robot applications: An immersive virtual reality approach.

Unmanned Aerial Vehicles (UAVs) exhibit great agility but usually require an experienced pilot to operate them in certain applications such as inspection for disaster scenarios or buildings. The reduction of cognitive overload when driving this kind of aerial robot becomes a challenge and several solutions can be found in the literature. A new virtual control scheme for reducing this cognitive overload when controlling an aerial robot is proposed in this paper. The architecture is based on a novel interaction Drone Exocentric Advanced Metaphor (DrEAM) located in a Cave Automated Virtual Environment (CAVE) and a real robot containing an embedded controller based on quaternion formulation. The testing room, where real robots are evolving, is located away from the CAVE and they are connected via UDP in a ground station. The user controls manually a virtual drone through the DrEAM interaction metaphor, and the real robot imitates autonomously in real time the trajectory imposed by the user in the virtual environment. Experimental results illustrate the easy implementation and feasibility of the proposed scheme in two different scenarios. Results from these tests show that the mental effort when controlling a drone using the proposed virtual control scheme is lower than when controlling it in direct view. Moreover, the easy maneuverability and controllability of the real drone is also demonstrated in real time experiments.

Benchmark Evaluation of Hybrid Fixed-Flapping Wing Aerial Robot With Autopilot Architecture for Autonomous Outdoor Flight Operations

Benchmark Evaluation of Hybrid Fixed-Flapping Wing Aerial Robot With Autopilot Architecture for Autonomous Outdoor Flight Operations

Quadrolltor: A Reconfigurable Quadrotor With Controlled Rolling and Turning

This letter reports an aerial robot–Quadrolltor, with the ability to roll and turn. Existing bimodal quadrotors feature cylindrical rolling cages that are rotationally decoupled from the robot's main rigid body. In contrast, the proposed robot employs passively reconfigurable structures to enable the second mode of locomotion, tightly coupling the attitude of the robot to the rolling cage. The benefits are precise rolling and turning control as well as improved rolling efficiency. Experiments were conducted to comprehensively validate the hybrid locomotion. The robot leveraged the superior maneuverability in the rolling mode to take photos of the surroundings at different tilting and panning angles to construct a panoramic image. Besides, the results of the power measurements show a significant reduction in the cost of transport brought by at low speed, equating to a 15-fold extension in the operational range.

Scalability of Cyber-Physical Systems with Real and Virtual Robots in ROS 2.

Nowadays, cyber-physical systems (CPSs) are composed of more and more agents and the demand for designers to develop ever larger multi-agent systems is a fact. When the number of agents increases, several challenges related to control or communication problems arise due to the lack of scalability of existing solutions. It is important to develop tools that allow control strategies evaluation of large-scale systems. In this paper, it is considered that a CPS is a heterogeneous robot multi-agent system that cooperatively performs a formation task through a wireless network. The goal of this research is to evaluate the system's performance when the number of agents increases. To this end, two different frameworks developed with the open-source tools Gazebo and Webots are used. These frameworks enable combining both real and virtual agents in a realistic scenario allowing scalability experiences. They also reduce the costs required when a significant number of robots operate in a real environment, as experiences can be conducted with a few real robots and a higher number of virtual robots by mimicking the real ones. Currently, the frameworks include several types of robots, such as the aerial robot Crazyflie 2.1 and differential mobile robots Khepera IV used in this work. To illustrate the usage and performance of the frameworks, an event-based control strategy for rigid formations varying the number of agents is analyzed. The agents should achieve a formation defined by a set of desired Euclidean distances to their neighbors. To compare the scalability of the system in the two different tools, the following metrics have been used: formation error, CPU usage percentage, and the ratio between the real time and the simulation time. The results show the feasibility of using Robot Operating System (ROS) 2 in distributed architectures for multi-agent systems in experiences with real and virtual robots regardless of the number of agents and their nature. However, the two tools under study present different behaviors when the number of virtual agents grows in some of the parameters, and such discrepancies are analyzed.

Stabilizing Aerodynamic Dampers for Cooperative Transport of a Suspended Payload with Aerial Robots

The current paper addresses the problem of stabilizing multiple aerial robots cooperatively transporting a cable‐suspended payload by an aeromechanic method. Instead of relying on global navigation satellite systems (GNSS) or vision and communication for agents to actively estimate and control the state of the multibody dynamics, lightweight air dampers to make the multiagent system inherently stable at its equilibrium state, permitting the robots to safely carry a load at a constant velocity are employed. This is achieved without additional state estimation or active correction. The proposed framework is proven stable and verified by simulations and extensive flight experiments. Lightweight mechanical dampers (under 7 g) are shown to be effective in attenuating undesired oscillations and overcoming disturbances. To this end, a team of four robots cooperatively transporting a payload over 20 m in open space is demonstrated, and three robots safely transporting a point‐mass payload over a distance of 45 m outdoors. The promising outcomes highlight the benefits of the passive strategy, which demands minimal hardware components and computation to realize the sophisticated aerial transport task.

The proof of concept of uninterrupted push‐pull electromagnetic propulsion and energy conversion systems for drones and planet landers

AbstractAlthough numerous models of aerial‐robots/drones and planet landers have been demonstrated to fly autonomously in natural and manmade environments for far‐reaching scientific and technological change to help humankind, no drone flowed yet with a push‐pull dual‐head electromagnetic propulsion (EMP) system ensuring unrestricted flight endurance. The precept of EMP is eminent as it hastens an object using a flowing electrical current, either to charge a field or opposing a magnetic field for locomotive use. Here we present a proof of concept to demonstrate the capability of a newly invented variable speed propulsion and energy conversion system for uninterruptedly generating the reciprocating motion of a magnetic piston by a solar battery‐driven polarity changer timing circuit together with a laser‐based timing circuit for redundancy. The reciprocating crusade of the magnetic piston could be successfully converted into rotary motion to generate continuous power for various multidisciplinary applications on Earth and the other planets effectively in lieu of long‐lasting rechargeable batteries. The proposed concept can also be used for devising various systems and subsystems from underwater to outer space by using light weight supermalloy, which ensures high magnetic fluxes with relatively low current. Lucrative applications include nanomaterial‐enabled locomotive applications. Aerial robots regulated with the EMP system could be used for fostering pharmaceutical florae in the international space station for drug design to negate the recently discovered phenomenon of Sanal flow choking in cardiovascular system at gravity and/or microgravity conditions. This concept is originated from mind and aimed for lucrative product developments of yocto to yotta scale energy systems and beyond by discovering new magnetic materials through the fourth industrial revolution. Herein, a proof of the concept of an unrestricted solar‐battery driven push‐pull electromagnetic propulsion and energy conversion device by use of light weight high power magnetic materials is presented.