Robotic grippers are increasingly deployed across industrial, collaborative, and aerial platforms, where each embodiment imposes distinct mechanical, energetic, and operational constraints. Established YCB and NIST benchmarks quantify grasp success, force, or timing on a single platform, but do not evaluate cross-embodiment transferability or energy-aware performance - essential for modern mobile and aerial manipulation. This letter introduces the Cross-Embodiment Gripper Benchmark (CEGB), a reproducible benchmarking suite extending YCB and selected NIST metrics with three additional components: a transfer-time benchmark measuring embodiment exchange effort, an energy-consumption benchmark evaluating grasping and holding efficiency, and an intent-specific ideal payload assessment. Together, these metrics characterize grasp performance and cross-platform suitability. CEGB is validated on two mechanically distinct grippers. The experimental evaluation quantifies embodiment-dependent differences in transfer time, energetic efficiency, and operational capability under unified statistical reporting. CEGB provides a reproducible foundation for cross-platform, energy-aware gripper evaluation.

This paper presents a novel computational framework for the design of closed-loop guidance and control laws in highly uncertain environments, possibly characterized by unmodeled dynamics and external disturbances. The proposed methodology integrates the use of Gaussian process regression (GPR) to model uncertainties within a stochastic optimal control framework. GPR provides a probabilistic approach to disturbance estimation using simulated or observed data to characterize noise as a Gaussian process. Convexification techniques are used to transform the original nonconvex stochastic control problem into a sequence of deterministic convex problems that can be efficiently solved by state-of-the-art interior-point algorithms. As a study case, the docking maneuver between an active chaser spacecraft and a passive target spacecraft in the presence of differential drag, with uncertainty in the ballistic coefficient, is considered. The obtained numerical results suggest the effectiveness of the proposed approach in compensating for the disturbances and driving the system to the target final distribution.

This paper describes the design, development, and validation of a 40 by 40 cm size, 2.2 kg weight autonomous aerial delivery robot intended to conduct intra-logistics operations with light parcels (under 250 grams) that can be safely delivered directly to the people on flight. The aerial robot is fed by power cable to overcome the limitations of batteries while increasing the payload-to-weight ratio, covering the propellers with the carbon fiber frame structure and foam protection to avoid the potential damage in case of collision with the people or the environment. A comparison of the proposed design with respect to our previous prototypes is presented along with the related works to motivate the design choices. The aerial robot implements and compares two onboard localization and mapping methods: RTAB-Map with RGB-D camera and 2D LiDAR, and FAST-LIO2 with 3D LiDAR. The platform is validated in two indoor mockup scenarios executing two different tasks. In the first one, the aerial robot is equipped with a hook for retrieving a parcel from a shelf, whereas in the second scenario a parcel is delivered through the window of a user's home.

This tutorial paper explains how to develop a ROS2 Gazebo simulator of a dual arm aerial manipulation robot intended to conduct parcel delivery operations in a representative intra-logistics scenario. This work follows a real-to-sim approach in the sense that the simulator replicates the aerial robot, scenario, and operation carried out by a fullyautonomous dual arm aerial delivery robot [1] during the euROBIN Project Cooperative Competition. The aerial robot consists of a quad-rotor platform controlled with the PX4 flight control software, equipped with a lightweight and human-size dual arm manipulator providing two joints per arm (shoulder and elbow pitch flexion/extension), integrating a camera for parcel detection and localization with Aruco markers, and a 2D LiDAR for localization and mapping. The paper outlines the process of creating the ROS2 simulator package from the 3D model and physical parameters of the robot and the objects in the scenario relying on the examples from PX4, including a 3D mesh of the flying arena scanned from the real scenario. The purpose of this work is to serve as guideline for students and young researchers in the development of an aerial robot simulator.

This paper presents the design, development, and validation of a fully autonomous dual-arm aerial robot capable of mapping, localizing, planning, and grasping parcels in an intra-logistics scenario. The aerial robot is intended to operate in a scenario comprising several supply points, delivery points, parcels with tags, and obstacles, generating the mission plan from the voice commands given by the user. The paper derives a transferability model of the scenario, the robot, and the task, so that the proposed system design can be generalized to different scenarios (environment transfer) and platforms (embodiment transfer). The proposed transferable system architecture allows the integration of software modules managed by the Aerial Delivery Robot Operations Manager (ADROM) through the Module Interface Instances (MII) that handle the requests and the signals involved during the execution of the operation. The performance of the developed system was evaluated as part of the euROBIN Nancy Competition, conducting more than 50 flight tests. The software modules are open source, making the flight dataset also publicly available.

Unmanned aerial vehicles (UAVs) operating in uncertain environments must plan safe and efficient trajectories while avoiding obstacles. This work addresses this challenge by formulating UAV path planning as a stochastic optimal control problem using covariance control. The objective is to generate a closed-loop guidance policy that steers both the mean and covariance of the UAV’s state toward a desired target distribution while ensuring probabilistic collision avoidance with ellipsoidal obstacles. The stochastic problem is convexified and reformulated as a sequence of deterministic optimization problems, enabling efficient computation even from coarse initial guesses. Simulation results demonstrate that the proposed method successfully produces robust trajectories and feedback policies that satisfy chance constraints on obstacle avoidance and reach the target with prescribed statistical characteristics.

This paper shows how different types of novel aerial robots with new functionalities can cooperate in the inspection and maintenance (I&M) of power lines, one of the largest and most essential civil infrastructures in any country. This study relies on the results from the AERIAL-CORE research and innovation project. The paper describes an I&M validation scenario and evaluation metrics for three linked operation domains: 1) long-range inspection for the detection of possible damages on power lines in a post-storm scenario, 2) aerial manipulation for the installation of devices on power lines, and 3) aerial co-working to help human operators in their activities at height. It presents the demonstration of ten different aerial robots in a real scenario with 10 km of power lines. The platforms include morphing-wing and VTOL (vertical take-off and landing) UAVs (unmanned aerial vehicles), multi-rotors, and aerial manipulators. These platforms, custom-developed or commercially available, are evaluated in the three application domains, describing the new functionalities implemented for each case. The paper ends with guidelines, design principles, and lessons learned for future developments derived from the final demonstration of the project.

This paper presents the integration of a Variable Stiffness Link (VSL) for long-reach aerial manipulation, enabling adaptable mechanical coupling between an aerial multirotor platform and a dual-arm manipulator. Conventional long-reach manipulation systems rely on rigid or cable connections, which limit precision or transmit disturbances to the aerial vehicle. The proposed VSL introduces an adjustable stiffness mechanism that allows the link to behave either as a flexible rope or as a rigid rod, depending on task requirements. The system is mounted on a quadrotor equipped with the LiCAS dual-arm manipulator and evaluated through teleoperated experiments, involving external disturbances and parcel transportation tasks. Results demonstrate that varying the link stiffness significantly modifies the dynamic interaction between the UAV and the payload. The flexible configuration attenuates external impacts and aerodynamic perturbations, while the rigid configuration improves positional accuracy during manipulation phases. These results confirm that VSL enhances versatility and safety, providing a controllable trade-off between compliance and precision. Future work will focus on autonomous stiffness regulation, multi-rope configurations, cooperative aerial manipulation and user studies to further assess its impact on teleoperated and semi-autonomous aerial tasks.

This paper presents the design and development of an aerial-ground robotics testbed for simulating bimanual manipulation operations on orbit relying on aerial robotics platforms, considering as representative use case the capture and maintenance of a non-cooperative free-floating satellite. The proposed testbed design is intended to facilitate the realization of simulations involving physical interaction, taking benefit of the technologies derived from aerial robotic manipulation, to be used as a complementary or alternative solution to existing ground testbed facilities. The system consists of a fully actuated multi-rotor (FAMR) that emulates the free flying/free floating dynamics of a target satellite, and a lightweight and compliant anthropomorphic dual arm system (LiCAS) to conduct the manipulation task, implementing the dynamics simulation in Simscape Multibody. The human-size and human-like kinematics of the LiCAS allow to replicate the manipulation skills of human operators, whereas its very low weight (2.5 kg) makes it possible to mount it on lightweight industrial robotic arms used to reproduce the spacecraft motion. Two types of compliant interactions are considered. On the one hand, impedance control for the post-contact phase is implemented in the simulation layer, using the right arm to hold the target and maintain the relative pose with the base while the left arm conducts the manipulation task. On the other hand, collision detection and passive accommodation is evaluated in the physical testing system relying on the mechanical joint compliance of the LiCAS dual arm. Collision reflexes between the free-floating FAMR and the compliant arm will be also experimentally evaluated by applying the principle of momentum conservation on the multi-rotor. The proposed approach takes benefit of the similarities between space and aerial robotic manipulation in terms of dynamic modeling, presenting simulation and experimental results in an indoor testbed to validate the developed framework.

Logistics and service operations involving parcel preparation, delivery, and unpacking from a supply point to a user's home could be carried out completely by robots in the near future, taking advantage of the capabilities of the different robot morphologies for the logistics, outdoor, and domestic environments. The use of robots for parcel delivery can contribute to the goals of sustainability and reduced emissions by exploiting their different locomotion modalities (wheeled, legged, and aerial). This article reports the development and results obtained from the first robotics hackathon celebrated as part of the European Robotics and Artificial Intelligence Network involving eight robotic platforms in three domains: 1) an industrial robotic arm for parcel preparation at the supply point, 2) a Centauro robot, a dual-arm aerial manipulator, and a wheeled-legged quadruped for parcel transportation, and 3) two humanoid robots and two commercial mobile manipulators for parcel delivery and unpacking in domestic scenarios. The article describes the joint operation and the evaluation scenario, the features and capabilities of the robots, particularly those involved in the realization of the tasks, and the lessons learned.

This paper presents the application of an aerial-deployable dual arm rolling robot developed for the realization of maintenance operations on power lines, validated through field tests in a real power line. The system consists of a quadrotor used as carrier platform for the transportation, deployment and retrieval of a lightweight and compliant anthropomorphic dual arm system (LiCAS). The arms are equipped with a drive wheel that allows them to move along the cable to conduct the installation of devices while the aerial platform stays at the landing area. The proposed approach avoids the problems of operating while flying in terms of positioning accuracy and energy efficiency, reducing also significantly the load on the power line compared to the case in which the multi-rotor has to perch. The paper describes the mechanisms implemented for the deployment and retrieval of the arms on the power line and for the installation of a customized model of bird flight diverter on the power line, as well as the system architecture, reporting results and practical aspects derived from the experimental validation.

This paper presents the modeling, control, and simulation of a flapping wing aerial platform equipped with a perching-launching mechanism and a two-degree-of-freedom (DoF) robotic arm intended to conduct manipulation tasks in outdoor scenarios which provide linear support structures for perching, considering as representative application example the contact inspection on power lines. The operation can be divided in four phases: 1) gliding towards the line, 2) perching, 3) manipulation, and 4) launching for flying again. A model of the system is derived and particularized for each phase, relying on numerical methods for simulating the perching and launching phases, following the Lagrange formulation for the equivalent planar manipulator once perched. A state-dependant Riccati equation (SDRE) controller is implemented on the robotic arm to conduct the manipulation task, taking into account that the passive pitch rotation of the base introduces an underactuated dynamics when perched. The model of the system, implemented in Simscape, is validated in simulation.

This paper introduces a novel approach for regulating the pose of a free-flying dual-arm anthropomorphic space manipulator system (SMS) using a finite-time state-dependent Riccati equation (SDRE) controller. The proposed system finds applications in on-orbit satellite inspection, servicing, space structure assembly, and debris manipulation. The dual-arm SMS presented in this work consists of two 7 degrees of freedom (DoF) robotic arms mounted on a free-flying spacecraft, resulting in a complex 20-DoF system. Due to the high number of DoFs, advanced controller design and efficient computations are necessary. The finite-time SDRE controller relies on the state-dependent coefficient (SDC) parameterization matrices, which are nonlinear apparent linearizations of the dynamics. Conventionally, the computation of SDC matrices is offline and relies on the a priori derivation of the analytical equations governing the dynamics of the system. However, this strategy becomes computationally impractical for high DoF plants. To overcome this issue and deliver a more viable solution, a numerical method to construct and update the SDC matrices at each time step is presented. This approach relies on a screw-theory-based recursive Newton-Euler algorithm designed to reconstruct the manipulator inertia and Coriolis matrices. These quantities are the building blocks of the SDC parameters used in the synthesis of the SDRE controller. Simulation results demonstrate the performances of the finite-time SDRE controller augmented with the online update of the state-dependent coefficients.

This paper presents a framework for simulating the visual tracking of low orbit space platforms such as satellites to be captured by a space manipulator system intended to conduct assembly, maintenance, or deorbiting operations. The video stream from the International Space Station, publicly available, is used as background for an animated overlay of the target platform moving within the field of view of the camera. A real-synthetic video is generated in Blender in different daytime observation conditions, allowing also the introduction of light sources for simulating the sun or its reflection of Earth's surface. Additionally, completely synthetic videos are created using a rendered model of the Earth, which allows for a variety of relative orientations for the camera. In order to illustrate the application of the developed framework with a particular visual tracking method, the Continuously Adaptive Mean-Shift (CAMShift) algorithm is evaluated considering a satellite platform as the target to be tracked with different approaching trajectories, illumination conditions, and background. The initial detection phase in dark scenes is enhanced introducing a Fast Line Detector (FLD) stage in a modified implementation, exploiting the linear segments typically found on satellites and solar panel arrays. The performance of the algorithm is evaluated in different conditions using the generated videos.

This paper proposes rigid-body modelling and identification procedures for long-reach dual-arm manipulators in a cable-suspended pendulum configuration. The proposed model relies on a virtually constrained open kinematic chain and lends itself to be simulated through the most commonly used robotic simulators without explicitly account for the cables constraints and flexibility. Moreover, a dynamic parameters identification procedure is devised to improve the simulation model fidelity and reduce the sim-to-real gap for controllers deployment. We show the capability of our model to handle different cable configurations and suspension mechanisms by customising it for two representative cable-suspended dual-arm manipulation systems: the LiCAS arms suspended by a drone and the CRANEbot system, featuring two Pilz arms suspended by a crane. The identified dynamic models are validated by comparing their evolution with data acquired from the real systems showing a high (between 91.3% to 99.4%) correlation of the response signals. In a comparison performed with baseline pendulum models, our model increases the simulation accuracy from 64.4% to 85.9%. The simulation environment and the related controllers are released as open-source code.

This paper presents the design, development, and validation in indoor scenario of an aerial delivery system intended to conduct the delivery of light parcels directly to the user through the window of his/her home, motivated by the convenience of facilitating the access to medicines to people with reduced mobility.The system consists of a fully-actuated multi-rotor (FAMR) equipped with a front basket where the parcel to be delivered is loaded by a lightweight and compliant anthropomorphic dual arm system (LiCAS) located at the supply point, using one of the arms to drop the parcel in the basket while the other arm holds its base to support the sudden moment exerted at the FAMR. The paper analyses four types of physical interactions raised during the operation on flight: (1) sudden changes in the mass distribution of the FAMR during the load/unload phase, affecting the multi-rotor position-attitude controllers, (2) impact and impulsive forces exerted by the human on the FAMR to demonstrate the reliability and robustness of conventional cascade controllers, (3) passive accommodation of the LiCAS while holding the FAMR during the parcel load, relying on the mechanical joint compliance, and (4) compliant human–FAMR interaction, interpreting the multi-rotor pose control error as a Cartesian/angular deflection to implement an admittance controller that allows the user guiding the platform. Experimental results allow the identification and characterization of these effects for different payload masses. The execution of the complete operation, involving the parcel load with the LiCAS and handover by the user through a window, is validated in a representative indoor scenario.

Large-scale infrastructures are prone to deterioration due to age, environmental influences, and heavy usage. Ensuring their safety through regular inspections and maintenance is crucial to prevent incidents that can significantly affect public safety and the environment. This is especially pertinent in the context of electrical power networks, which, while essential for energy provision, can also be sources of forest fires. Intelligent drones have the potential to revolutionize inspection and maintenance, eliminating the risks for human operators, increasing productivity, reducing inspection time, and improving data collection quality. However, most of the current methods and technologies in aerial robotics have been trialed primarily in indoor testbeds or outdoor settings under strictly controlled conditions, always within the line of sight of human operators. Additionally, these methods and technologies have typically been evaluated in isolation, lacking comprehensive integration. This paper introduces the first autonomous system that combines various innovative aerial robots. This system is designed for extended-range inspections beyond the visual line of sight, features aerial manipulators for maintenance tasks, and includes support mechanisms for human operators working at elevated heights. The paper further discusses the successful validation of this system on numerous electrical power lines, with aerial robots executing flights over 10 kilometers away from their ground control stations.