GPS is widely used for the localization of unmanned aerial vehicles due to its universal nature and high precision when combined with an IMU. However, a GPS relies on communication with satellites, and in some scenarios, this communication can be blocked rendering the method unusable. In these scenarios, an alternative localization method is needed as relying entirely on an IMU-based approach results in high degrees of drift. A solution to this problem is using a camera, to track the takeoff position of the UAV, and utilizing the pin-hole model to estimate the distance to the takeoff position. The greatest strength of this solution is that the UAV can locate itself without relying on communication. However, there are several challenges associated with utilizing a single camera for localization, especially at long distances, as the noise quickly grows. This paper presents a solution to this problem and a real-life implementation displaying the viability of the method.

Fiducial markers play a common role in robotics, but their usability is constrained by the distance they can operate in. This limitation arises from the pixel count necessary for accurate detection. This paper presents a fiducial marker designed to be identifiable from just a few pixels. The proposed marker utilizes colors to improve the certainty of the detection while keeping the features of the marker as simple as possible. Experiments have been conducted to show the range in which the proposed marker can be used compared to the popular ArUco marker.

Recently, the utilization of aerial manipulators for performing pushing tasks in non-destructive testing (NDT) applications has seen significant growth. Such operations entail physical interactions between the aerial robotic system and the environment. End-effectors with multiple contact points are often used for placing NDT sensors in contact with a surface to be inspected. Aligning the NDT sensor and the work surface while preserving contact, requires that all available contact points at the end-effector tip are in contact with the work surface. With a standard full-pose controller, attitude errors often occur due to perturbations caused by modeling uncertainties, sensor noise, and environmental uncertainties. Even small attitude errors can cause a loss of contact points between the end-effector tip and the work surface. To preserve full alignment amidst these uncertainties, we propose a control strategy which selectively deactivates angular motion control and enables direct force control in specific directions. In particular, we derive two essential conditions to be met, such that the robot can passively align with flat work surfaces achieving full alignment through the rotation along non-actively controlled axes. Additionally, these conditions serve as hardware design and control guidelines for effectively integrating the proposed control method for practical usage. Real world experiments are conducted to validate both the control design and the guidelines.

Pushing tasks performed by aerial manipulators can be used for contact-based industrial inspections. Underactuated aerial vehicles are widely employed in aerial manipulation due to their widespread availability and relatively low cost. Industrial infrastructures often consist of diverse oriented work surfaces. When interacting with such surfaces, the coupled gravity compensation and interaction force generation of underactuated aerial vehicles can present the potential challenge of near-saturation operations. The blind utilization of these platforms for such tasks can lead to instability and accidents, creating unsafe operating conditions and potentially damaging the platform. In order to ensure safe pushing on these surfaces while managing platform saturation, this work establishes a safety assessment process. This process involves the prediction of the saturation level of each actuator during pushing across variable surface orientations. Furthermore, the assessment results are used to plan and execute physical experiments, ensuring safe operations and preventing platform damage.

Operating unmanned aerial vehicles (UAVs) for assets inspections poses distinct challenges encompassing the need to maintain a safe distance from the inspection area, ensure correct orientation towards the inspected surface, and achieve comprehensive coverage of the entire surface. Achieving these tasks is inherently complex and stressful. Therefore, a novel approach that seeks to enhance the piloting experience by harnessing the latest advancements in segmentation models, such as Segment Anything Model (SAM), is proposed. These models, thanks to their prompting capabilities, allow seamless communication between the operator and the UAV, opening up the possibility of defining intricate inspection regions through simple interactions. Within this approach, decision-making authority remains with the operator, while the UAV takes on the demanding task of segmenting the designated area and devising an appropriate traversal plan. Throughout this process, the operator’s situational awareness is heightened through visual cues overlaid on the camera stream and a 3D panel presenting information of the drone position and spatially sensed data. This teleoperation framework allows the operator to maintain continuous control of the ongoing operation through a simplified interface. The paper delineates both the system and the methodology employed, showcasing the effectiveness of integrating segmentation models into the decision-making workflow. The validity of the proposed framework is established through testing within a photorealistic UAV simulator along with real experiments in a controlled laboratory environment.

Aerial robots have been widely used as sensor carrying platforms in a wide range of application, mainly because using this type of systems for physical interaction seems to be an unsuitable operation. This is not only due to the risk of collision and damage of the platform, but also because it is unclear whether a consumer-grade UAV can withstand physical contact with the environment. In this paper, we address the issue of performing physical interaction with the environment by a multirotor UAV implementing a basic cascaded position-attitude controller, typical of most of consumer-grade multirotor systems. Precisely, we identify mathematically the boundaries where the system can safely be used to perform physical interaction with the environment. The theoretical approach is finally validated through experiments showing that physical contact can only be achieved within a predefined region of control inputs.

The application of robotic solutions to small-batch production is challenging: economical constraints tend to dramatically limit the time for setting up new batches. Organizing robot tasks into modular software components, called skills, and allowing the assignment of multiple concurrent tasks to a single robot is potentially game-changing. However, due to cycle time constraints, it may be necessary for a skill to take over without waiting on another to terminate, and the available literature lacks a systematic approach in this case. In the present article, we fill the gap by (a) establishing the specifications of skills that can be sequenced with partial executions, (b) proposing an implementation based on the combination of finite-state machines and behavior trees, and (c) demonstrating the benefits of such skills through extensive trials in the environment of ARIAC (Agile Robotics for Industrial Automation Competition).

Task level programming based on skills has often been proposed as a mean to decrease programming complexity of industrial robots. Several models are based on encapsulating complex motions into self-contained primitive blocks. A semantic skill is then defined as a deterministic sequence of these primitives. A major limitation is that existing frameworks do not support the coordination of concurrent motion primitives with possible interference. This decreases their reusability and scalability in unstructured environments where a dynamic and reactive adaptation of motions is often required. This paper presents a novel framework that generates adaptive behaviors by modeling skills as concurrent motion primitives activated dynamically when conditions trigger. The approach exploits the additive property of motion generators to superpose multiple contributions. We demonstrate the applicability on a real assembly use-case and discuss the gained benefits.

In the field of aerial robotics, one of the key challenges is to enable aerial manipulators to exert substantial forces on the environment. Enabling this will allow the technology to perform meaningful tasks airborne, such as cleaning or grinding surfaces. While in contact and applying a large, continuous force, control of the UAV's attitude is a challenge. In this work, we show that a regular (PID-based) attitude controller is incapable of stabilizing aerial manipulators that apply physical contact forces on the environment that are comparable to the UAV's weight. We present a novel control algorithm that uses an LQR-optimized state feedback on the roll and yaw angle while in contact. Experiments on a UAV of 1.5 kg show that the proposed controller is capable of applying a contact force of over 15 N - equal to the UAV's weight - sustained for several minutes.

This paper presents the mechatronic design of a robotic arm that is mounted on a ground rover and used to deploy and recover small-scale unmanned aerial vehicles. The arm and rover are part of a network of collaborative robotic agents aiming to enhance current rescue operations by supporting human operators without burdening them with servicing tasks. The robust autonomy of the system, guaranteed in part through the addition of this robotic arm, is a main contributing factor. Design requirements are derived from the context of the rescue mission and a kinematic analysis is provided that leads to a customized design, including variable stiffness joints for compliant interaction with the environment. Experiments demonstrate the system's ability to perform the required Cartesian trajectory control and manipulation tasks, and to achieve a desired variable end-effector compliance.

The increasing use of Variable Stiffness Actuators (VSAs) in robotic joints is helping robots to meet the demands of human-robot interaction, requiring high safety and adaptability. The key feature of a VSA is the ability to exploit internal elastic elements to obtain a variable output stiffness. These allow the joints to store mechanical energy supplied through interaction with the environment and make the system more robust, efficient, and safe. This paper discusses the design of leaf springs for a sub-class of VSAs that use variable lever arm ratios as means to change their output stiffness. Given the trade-off between compactness and the maximum energy storage capacity, the internal springs' dimensions and material choice are assessed through a theoretical analysis and practical experiments.

The paper focuses on the mechatronic design of a robotic manipulator that is meant to be mounted on an Unmanned Aerial Vehicle (UAV) and to be used in industrial applications, for both aerial inspection by contact and aerial manipulation. The combination of an UAV and the robotic manipulator realizes the aerial manipulator. The robotic manipulator is designed to be versatile so that the aerial manipulator can perform both trajectory tracking in free flight and physical interaction. Moreover, the robotic manipulator can be mounted on commercially available UAVs a modular way without interfering with the existing onboard control architecture. Experimental test are validating the overall mechatronic design.

Variable stiffness actuators (VSA) are fostered in robotics for their capability to address physical interaction with a physically adjustable compliance, being advantageous in terms of efficiency, safety and adaptability to unknown environments. Here we introduce the concept of a switching VSA (sVSA), in which a single actuator is used to control the position or the stiffness of a robotic joint according to a mechanical switch. Despite not allowing simultaneous control of both quantities, this architecture has the potential to make the design lighter, requiring one continuously powered actuator, controllable in position, and one additional switch, activated only occasionally between two limit stages: the advantages are the separation of the motors power requirements and a simpler control. A first prototype of a 1-DoF revolute variable-stiffness joint has been built, based on the vsaUT-II developed at the University of Twente, with a novel clutch mechanism allowing continuous and efficient switching. The prototype proved functionality and feasibility of the sVSA concept.

This paper proposes a semi-autonomous bilateral control architecture for unmanned aerial vehicles. During autonomous navigation, a human operator is allowed to assist the autonomous controller of the vehicle by actively changing its navigation parameters to assist it in critical situations, such as navigating through narrow paths. The overall goal of the controller is to combine the stability and precision of an autonomous control with the cognitive abilities of a human operator, only when strictly required for the accomplishment of a task. The control architecture has been validated through simulations and experiments.

In robotics, differential mechanisms are widely used when lightweightness and compactness are a requisite for the robot design. Moreover, the last decades have seen the rise of (variable) compliant acuators as important elements to perform safe interaction and dynamic tasks. This paper introduces a Variable Stiffness Differential Drive (VSDD), i.e., a differential transmissions with variable stiffness actuators (VSAs), and presents a dynamic analysis. The analysis shows that, when variable stiffness actuators are used in coupled differential transmissions, the allowable stiffness range at the output of the system depends on the position of the springs inside the device. In particular, independent output joint stiffness can be obtained by dislocating the actuation from the elastic elements.

In this paper, we present the design, simulation and experimental validation of a control architecture for an unmanned aerial vehicle endowed with a manipulation system and interacting with a remote environment. The goal of this work is to show that the interaction control allows the manipulator to track a desired force, normal to a vertical wall, while still maintaining the possibility of moving on the wall. The control strategy has been implemented and validated in simulations and experiments on the manipulator standalone, i.e., attached to a fixed base, and on the manipulator attached to the aerial vehicle.

This paper proposes a modified impedance control strategy for a generic robotic system that can interact with an unknown environment or can be moved by a human. The controller makes use of a virtual mass, coupled to the robotic system, which allows for stable interaction. The focus is mainly on unmanned aerial vehicles that are required to get into contact with the environment to perform a specific task on it and that can be shifted by humans. The control architecture is validated both in simulations, on a 1-dimensional benchmark, and in experiments on a real quadrotor flying vehicle.

In this paper, we present the mechanical design and modeling of a manipulation system for unmanned aerial vehicles, which have to physically interact with environments and perform ultrasonic non-destructive testing experiments and other versatile tasks at unreachable locations for humans. The innovation of the prototype lies in the use of a three degrees of freedom Delta robotic manipulator together with a nondestructive testing end-effector, realized by a Cardan gimbal that allows the ultrasonic sensor to compliantly interact with the remote environment. The Cardan gimbal is endowed with a small actuator for the roll motion of the end-effector, a compliant element in the direction of interaction and two passive rotational degrees of freedom with defined equilibria to overcome gravity and to define a stable zero reference. Simulation results of a ducted-fan unmanned aerial vehicle interacting with a wall validate the overall mechanical design.

This paper focuses on the modeling and control of a flying robot. The complete system, composed of a quadrotor unmanned aerial vehicle and a custom-made manipulator, has been designed for remote inspection by contact of industrial plants. The goal of this paper is to show the dynamical characteristics of the flying robot during tasks that require physical interaction, and to determine a control strategy that allows to safely interact with unknown environments. The methodology has been implemented on a real prototype and tested in an indoor area. Experimental results validate the proposed controller and show its effectiveness.

When a robot is required to safely interact with a physical environment, two approaches are typically reported in literature: using a force/torque sensor to regulate the interaction forces at the end effector, or integrating sensors in each robot joint to regulate their torques. In this paper we want to discuss the benefits and the disadvantages of the two approaches, showing a direct comparison between the information which can be obtained from the two categories of sensors. Results obtained on the new iCub arm, which integrates torque sensing capabilities at joint level will be presented and discussed.

This paper describes the control of a human-like robotic neck actuated with tendons. The controller regulates the length of the tendons to achieve a desired orientation of the neck and at the same time it maintains the tension of the tendons within certain limits. The solution we propose does not use any model of the system, but it relies on online learning of the different Jacobian mappings required by the controller. Learning, data acquisition and control are simultaneous; thus learning is completely autonomous, and purely online. We show that after enough iterations the controller produces straight trajectories in the task space and is able to maintain the tension of the tendons within safe limits.

During the last decades, interaction (with humans and with the environment) has become an increasingly interesting topic of research within the field of robotics. At the basis of interaction, a fundamental role is played by the ability to actively regulate the interaction forces. In this paper we propose a technique for controlling the interaction forces exploiting a proximal six axes force/torque sensor. The major assumption is the knowledge of the point where external forces are applied. The proposed approach is tested and validated on the four limbs of the iCub, a humanoid robot designed for research in embodied cognition. Remarkably, the proposed approach can be used to implement active compliance in other non passively back-drivable manipulators by simply inserting one or more force/torque sensor anywhere along the kinematic chain.

Online optimal planning of robotic arm movement is addressed. Optimality is inspired by computational models, where a “cost function” is used to describe limb motions according to different criteria. A method is proposed to implement optimal planning in Cartesian space, minimizing some cost function, by means of numerical approximation to a generalized nonlinear model predictive control problem. The Extended RItz Method is applied as a functional approximation technique. Differently from other approaches, the proposed technique can be applied on platforms with strict control temporal constraints and limited processing capability, since the computational burden is completely concentrated in an off-line phase. The trajectory generation on-line is therefore computationally efficient. Task to joint space conversion is implemented on-line by a closed loop inverse kinematics algorithm, taking into account the robot's physical limits. Experimental results, where a 4DOF arm moves according to a particular nonlinear cost, show the effectiveness of the proposed approach, and suggest interesting future developments.