In this work we propose an uncertainty-aware controller for the Fly-Crane system, a statically rigid cable-suspended aerial manipulator using the minimum number of aerial robots and cables. The force closure property of the Fly-Crane makes it ideal for applications where high precision is required and external disturbances should be compensated. The proposed control requires the knowledge of the nominal values of a minimum number of uncertain kinematic parameters, thus simplifying the identification process and the controller implementation. We propose an optimization-based tuning method of the control gains that ensures stability despite parameter uncertainty and maximizes the $H_\infty$ performance. The validity of the proposed framework is shown through real experiments.

This article studies how parametric uncertainties affect the cooperative manipulation of a cable-suspended beam-shaped load by means of two aerial robots not explicitly communicating with each other. In particular, this article sheds light on the impact of the uncertain knowledge of the model parameters available to an established communicationless force-based controller. First, we find the closed-loop equilibrium configurations in the presence of the aforementioned uncertainties, and then, we study their stability. Hence, we show the fundamental role played in the robustness of the load attitude control by the internal force induced in the manipulated object by nonvertical cables. Furthermore, we formally study the sensitivity of the attitude error to such parametric variations, and we provide a method to act on the load position error in the presence of uncertainties. Eventually, we validate the results through an extensive set of numerical tests in a realistic simulation environment, including underactuated aerial vehicles and sagging-prone cables, and through hardware experiments.

This work introduces the G-Fly-Crane, a proof-of-concept aerial multi-robot system designed to demonstrate the advantage of using multiple aerial robots as a valuable tool for novel construction techniques, not requiring the use of heavy engines and costly infrastructures. We experimentally demonstrate its capability to perform pick-and-place and manipulation tasks in a construction scenario, with an increased payload capacity and dexterity compared to the single robot case. The system is composed of three aerial robots connected to a platform by three pairs of cables. The platform is equipped with a gripper, enabling the grasping of objects. The paper describes in detail the hardware and software architecture of our prototype and explains the implemented control methods. A shared control strategy incorporates the human operator in the control loop, thus increasing the overall system reliability when performing complex tasks. The paper also discusses the next steps required to bring this technology from indoor laboratory conditions to real-world applications.

We present the control in physical interaction with the environment of a Cable-suspended Aerial Multi-Robot Manipulator (CS-AMRM) called the Fly-Crane, composed of three aerial vehicles towed to a platform by means of six cables. The control strategy enables the system to accurately and safely perform tasks involving expected or unexpected interactions between the platform and the environment, in the absence of dedicated force/torque sensors. A previously developed Inverse Kinematic Controller (IKC) is enhanced with an admittance framework, and contacts are estimated through a generalized momentum-based observer. To assess the validity of our approach, and to provide practical insights into the method, we perform extensive experimental tests, comprehending the admittance property shaping to modulate stiffness, damping, and virtual mass, as well as experiments in a more realistic scenario involving contacts between the Fly-Crane and the environment.

In this work, a 3D printed biocompatible micro-optofluidic (MoF) device for two-phase flow monitoring is presented. Both an air–water bi-phase flow and a two-phase mixture composed of micrometric cells suspended on a liquid solution were successfully controlled and monitored through its use. To manufacture the MoF device, a highly innovative microprecision 3D printing technique was used named Projection Microstereolithography (P$\mu$SL) in combination with the use of a novel 3D printable photocurable resin suitable for biological and biomedical applications. The concentration monitoring of biological fluids relies on the absorption phenomenon. More precisely, the nature of the transmission of the light strictly depends on the cell concentration: the higher the cell concentration, the lower the optical acquired signal. To achieve this, the microfluidic T-junction device was designed with two micrometric slots for the optical fibers’ insertion, needed to acquire the light signal. In fact, both the micro-optical and the microfluidic components were integrated within the developed device. To assess the suitability of the selected biocompatible transparent resin for optical detection relying on the selected working principle (absorption phenomenon), a comparison between a two-phase flow process detected inside a previously fully characterized micro-optofluidic device made of a nonbiocompatible high-performance resin (HTL resin) and the same made of the biocompatible one (BIO resin) was carried out. In this way, it was possible to highlight the main differences between the two different resin grades, which were further justified with proper chemical analysis of the used resins and their hydrophilic/hydrophobic nature via static water contact angle measurements. A wide experimental campaign was performed for the biocompatible device manufactured through the P$\mu$SL technique in different operative conditions, i.e., different concentrations of eukaryotic yeast cells of Saccharomyces cerevisiae (with a diameter of 5 $\mathsf{\mu }$m) suspended on a PBS (phosphate-buffered saline) solution. The performed analyses revealed that the selected photocurable transparent biocompatible resin for the manufactured device can be used for cell concentration monitoring by using ad hoc 3D printed micro-optofluidic devices. In fact, by means of an optical detection system and using the optimized operating conditions, i.e., the optimal values of the flow rate $FR=0.1$ mL/min and laser input power $P\in \{1,3\}$ mW, we were able to discriminate between biological fluids with different concentrations of suspended cells with a robust working ability $R^2=0.9874$ and $R_{adj}^2=0.9811$.

This work proposes a multi-objective polydimethylsiloxane (PDMS) micro-optofluidic (MoF) device suitably designed and manufactured through a 3D-printed-based master–slave approach. It exploits optical detection techniques to characterize immiscible fluids or microparticles in suspension inside a compartment specifically designed at the core of the device referred to as the MoF chamber. In addition, we show our novel, fast, and cost-effective methodology, dual-slit particle signal velocimetry (DPSV), for fluids and microparticle velocity detection. Different from the standard state-of-the-art approaches, the methodology focuses on signal processing rather than image processing. This alternative has several advantages, including the ability to circumvent the requirement of complex and extensive setups and cost reduction. Additionally, its rapid processing speed allows for real-time sample manipulations in ongoing image-based analyses. For our specific design, optical signals have been detected from the micro-optics components placed in two slots designed ad hoc in the device. To show the devices’ multipurpose capabilities, the device has been tested with fluids of various colors and densities and the inclusion of synthetic microparticles. Additionally, several experiments have been conducted to prove the effectiveness of the DPSV approach in estimating microparticle velocities. A digital particle image velocimetry (DPIV)-based approach has been used as a baseline against which the outcomes of our methods have been evaluated. The combination of the suitability of the micro-optical components for integration, along with the MoF chamber device and the DPSV approach, demonstrates a proof of concept towards the challenge of real-time total-on-chip analysis.