Search Results (25)

Aerial docking is a crucial capability for extending the autonomy and functionality of uncrewed aerial vehicles (UAVs), yet practical and robust docking mechanisms remain underdeveloped. Mid-air recovery also enables flexible multi-UAV cooperation across diverse mission scenarios. To address the core challenge of achieving reliable and precise airborne rendezvous, this paper proposes a control-driven approach supported by a complementary mechanical design. A Nonlinear Model Predictive Control (NMPC) framework is developed for the follower UAV, incorporating a velocity-penalty strategy to ensure the smooth and accurate tracking of the leader UAV based on GNSS guidance during the rendezvous phase. In the terminal docking stage, alignment accuracy is further enhanced through vision-based pose estimation using an ArUco marker array mounted on the leader UAV. Building on these algorithmic components, an improved active V-shaped docking mechanism is introduced to compensate for the follower UAV’s pitch angle during engagement, providing robustness against residual alignment errors. The feasibility and performance of the proposed system are validated through static ground docking experiments of the mechanical module and AirSim dynamic simulations evaluating the autonomous docking controller. Full article

This paper details the design of a guidance architecture, in the form of a layered, finite state machine, meant to enable safe and autonomous rendezvous operations. The onboard software uses relative state parametrization based on relative orbital elements which provide significant geometrical insight into the shape of the relative orbit. The development is structured in two main steps: first, novel closed-form impulsive control schemes, derived from the Gauss Variational Equations expressed in a velocity-aligned frame, are formulated. These complement available strategies from the literature and generalize them for arbitrarily eccentric reference orbits. Secondly, the definition of the guidance layer provides the chaser spacecraft with the capability to select, schedule, and execute the proper maneuvers to complete a given rendezvous scenario, ensuring operational safety and predictability. The functionality and performance of the implemented architecture are analyzed through numerical tests in a linear propagator and a high-fidelity non-linear simulator. The results provide validation of the developed maneuvers’ strategies, as well as demonstrating how the proposed guidance architecture can be used in a straightforward fashion across different target orbit scenarios, while guaranteeing the same level of passive safety. Full article

Developing autonomous technologies will enable humanity to considerably expand our lunar and space exploration capabilities. Along with the technical challenges of developing autonomous technologies, there is also the issue of trust—stakeholders are often resistant to their use for a variety of psychological reasons. Nevertheless, several successful methods for gradually building trust have been developed for both terrestrial and space applications. Relevant case studies provide insights on how trust is built for stakeholders when it comes to self-driving vehicles, Artificial Intelligence in aviation, space station operations, satellite rendezvous missions, and Mars rover surface operations. Based on these case studies, we propose a generalized method for building trust with stakeholders and have applied it to a lunar construction pathfinder mission currently in development. Metrics for assessing success criteria for autonomous systems are provided as a means to progress through the proposed phases of autonomy deployment. Full article

In this paper, we present a Unified Framework for cross-domain Space drone Pose Estimation (UF-SPE), addressing the simulation-to-reality gap that limits the deployment of deep learning models in real space missions. The proposed UF-SPE framework integrates offline domain generalization with online unsupervised domain adaptation. During offline training, the model relies exclusively on synthetic images. It employs advanced augmentation techniques and a multi-task architecture equipped with Domain Shifting Uncertainty modules to improve the learning of domain-invariant features. In the online phase, normalization layers are fine-tuned using unlabeled real-world imagery via entropy minimization, allowing for the system to adapt to target domain distributions without manual labels. Experiments on the SPEED+ benchmark demonstrate that the UF-SPE achieves competitive accuracy with just 12.9 M parameters, outperforming the comparable lightweight baseline method by 37.5% in pose estimation accuracy. The results validate the framework’s efficacy and efficiency for robust cross-domain space drone pose estimation, indicating promise for applications such as on-orbit servicing, debris removal, and autonomous rendezvous. Full article

The high-precision attitude estimation technique for non-cooperative targets in space, based on monocular cameras, has important application value in missions such as space debris removal, autonomous rendezvous and docking, and on-orbit services. However, due to the inherent missing information problem of monocular vision systems and the high complexity of target geometry, existing monocular pose estimation methods find it difficult to realize an effective balance between accuracy and computational efficiency. Current solutions commonly adopt deep neural network architectures to improve estimation accuracy; but, this method is often accompanied by the problems of a dramatic expansion of the number of model parameters and a significant increase in computational complexity, which limits its deployment and real-time inference capabilities in real spatial tasks. To address the above problems, this paper proposes a spacecraft pose estimation network, called Balance-URSONet, which weighs the trade-off between accuracy and the number of parameters, and makes the pose estimation model have a stronger feature extraction capability by innovatively using RepVGG as the feature extraction network. In order to effectively improve the performance and inference speed of the model, this paper proposes the feature excitation unit (FEU), which is able to flexibly adjust the feature representation of the network and thus optimize the utilization efficiency of spatial and channel information. The experimental results show that the Balance-URSONet proposed in this paper has excellent performance in the spacecraft pose estimation task, with an ESA score of 0.13 and a parameter count 13 times lower than that of URSONet. Full article

The fixed-time trajectory tracking control problem of the uncertain nonlinear Euler–Lagrange system is studied. To ensure the fast, high-precision trajectory tracking performance of this system, a non-singular terminal sliding-mode controller based on Gaussian process regression is proposed. The control algorithm proposed in this paper is applicable to periodic motion scenarios, such as spacecraft autonomous orbital rendezvous and repetitive motions of robotic manipulators. Gaussian process regression is employed to establish an offline data-driven model, which is utilized for compensating parametric uncertainties and external disturbances. The non-singular terminal sliding-mode control strategy is used to avoid singularity and ensure fast convergence of tracking errors. In addition, under the Lyapunov framework, the fixed-time convergence stability of the closed-loop system is rigorously demonstrated. The effectiveness of the proposed control scheme is verified through simulations on a spacecraft rendezvous mission and periodic joint trajectory tracking for a robotic manipulator. Full article

This paper addresses the autonomous rendezvous and docking between a chaser spacecraft and a target spacecraft. An optimal control method is employed to plan the rendezvous and docking maneuver, considering various constraints, including force, velocity, field of view, and collision avoidance with a diamond-shaped obstacle. The optimal trajectories are derived using a symplectic algorithm, which ensures high accuracy and enhances computational efficiency. These trajectories serve as the reference for the maneuver. A PD-based tracking control method is proposed to enable real-time feedback control. An air-bearing experimental system, encompassing state measurement, data transmission, and processing, is established to conduct ground-based tracking experiments. Furthermore, specialized simulators for the chaser and target spacecraft, equipped with a docking mechanism, are designed. Experimental results validate both the feasibility of the reference trajectories and the effectiveness of the PD tracking control approach. Full article

The aim of this research paper is to propose a framework to model, simulate and control the motion of a small spacecraft in the proximity of a space station. In particular, rendezvous in the presence of physical obstacles is tackled by a virtual potential theory within a modern manifold calculus setting and simulated numerically. The roto-translational motion of a spacecraft as well as the control fields are entirely formulated through a coordinate-free Lie group-type formalism. Likewise, the proposed control strategies are expressed in a coordinate-free setting through structured control fields. Several numerical simulations guide the reader through an evaluation of the most convenient control strategy among those devised in the present work. Full article

The accelerating deployment of spacecraft in orbit has generated interest in on-orbit servicing (OOS), inspection of spacecraft, and active debris removal (ADR). Such missions require precise rendezvous and proximity operations in the vicinity of non-cooperative, possibly unknown, resident space objects. Safety concerns with manned missions and lag times with ground-based control necessitate complete autonomy. This requires robust characterization of the target’s geometry. In this article, we present an approach for mapping geometries of satellites on orbit based on 3D Gaussian splatting that can run on computing resources available on current spaceflight hardware. We demonstrate model training and 3D rendering performance on a hardware-in-the-loop satellite mock-up under several realistic lighting and motion conditions. Our model is shown to be capable of training on-board and rendering higher quality novel views of an unknown satellite nearly 2 orders of magnitude faster than previous NeRF-based algorithms. Such on-board capabilities are critical to enable downstream machine intelligence tasks necessary for autonomous guidance, navigation, and control tasks. Full article

The development of autonomous guidance control and navigation systems for spacecraft would greatly benefit applications such as debris removals or on-orbit servicing, where human intervention is not practical. Within this context, inspired by Autonomous Vision Approach Navigation and Target Identification (AVANTI) demonstration, this work presents new guidance algorithms for rendezvous and proximity operations missions. Analytical laws are adopted and preferred over numerical methods, and mean relative orbital elements are chosen as state variables. Application times, magnitudes and directions of impulsive controls are sought to minimize propellant consumption for the planar reconfiguration of the relative motion between a passive target spacecraft and an active chaser one. In addition, simple and effective algorithms to evaluate the benefit of combining in-plane and out-of-plane maneuvers are introduced to deal with 3D problems. The proposed new strategies focus on maneuvers with a dominant change in the relative mean longitude (rarely addressed in the literature), but they can also deal with transfers where other relative orbital elements exhibit the most significant variations. A comprehensive parametric analysis compares the proposed new strategies with those employed in AVANTI and with the global optimum, numerically found for each test case. Results are similar to the AVANTI solutions when variations of the relative eccentricity vector dominate. Instead, in scenarios requiring predominant changes in the relative mean longitude, the required $\Delta$V exhibits a 49.88% reduction (on average) when compared to the original methods. In all the test cases, the proposed solutions are within 3.5% of the global optimum in terms of $\Delta$V. The practical accuracy of the presented guidance algorithms is also tested with numerical integration of equations of motion with J2 perturbation. Full article

In this paper, the problem of autonomous optimal absolute orbit keeping for a satellite mission in Low Earth Orbit using electric propulsion is considered. The main peculiarity of the approach is to support small satellite missions in which the platform is equipped with a single thruster nozzle that provides acceleration on a single direction at a time. This constraint implies that an attitude maneuver is necessary before or during each thrusting arc to direct the nozzle into the desired direction. In this context, an attitude guidance algorithm specific for the orbit maneuver has been developed. A Model Predictive Control scheme is proposed, where the attitude kinematics are coupled with the orbital dynamics in order to obtain the optimal guidance profiles in terms of satellite state, reference attitude, and thrust magnitude. The proposed control scheme is developed exploiting formation flying techniques where the reference orbit is that of a virtual spacecraft that the main satellite is required to rendezvous with. In addition to the controller design, the closed-loop configuration is presented supported by numerical simulations. The efficacy of the proposed autonomous orbit-keeping approach is shown in several application scenarios. Full article

As interest in Moon exploration grows, and efforts to establish an orbiting outpost intensify, accurate modeling of spacecraft dynamics in cislunar space is becoming increasingly important. Contrary to satellites in Low Earth Orbit (LEO), where it takes around 5 ms to communicate back and forth with a ground station, it can take up to 2.4 s to communicate with satellites near the Moon. This delay in communication can make the difference between a successful docking and a catastrophic collision for a remotely controlled satellite. Moreover, due to the unstable nature of trajectories in cislunar space, it is necessary to design spacecraft that can autonomously make frequent maneuvers to stay on track with a reference orbit. The communication delay and unstable trajectories are exactly why autonomous navigation is critical for proximity operations and rendezvous and docking missions in cislunar space. Because spacecraft computational hardware is limited, reducing the computational complexity of navigational algorithms is both desirable and often necessary. By the introduction of a linear system approach to the deputy spacecraft motion, this research avoids the computational burden of integrating the deputy relative equations of motion. In this research, the relative CR3BP equations of motion are derived and linearized using a matrix exponential approximation. This research continues the development of the matrix exponential linearized relative circular restricted three-body problem (CR3BP) equations by applying the dynamics model to estimation and control applications. A simulation is performed to compare state estimation results obtained from using the linearized equations of motion utilizing a Kalman filter and for state estimation utilizing an unscented Kalman filter with the full nonlinear equations of motion. The linearized exponential model is shown to be sufficient for state estimation in the presence of noisy measurements for an example scenario. Additionally, a linear quadratic regulator (LQR) controller was added to optimally control a deputy spacecraft to rendezvous with a chief spacecraft in cislunar space. The contribution of this work is twofold: to provide a proof of concept that the matrix exponential solution for the linearized relative CR3BP equations can be used as the dynamics model for state estimation, as well as to simulate an optimal rendezvous maneuver in the presence of measurement noise. Full article

Autonomous grounded vehicle-based social assistance/service robot parking in an indoor environment is an exciting challenge in urban cities. There are few efficient methods for parking multi-robot/agent teams in an unknown indoor environment. The primary objective of autonomous multi-robot/agent teams is to establish synchronization between them and to stay in behavioral control when static and when in motion. In this regard, the proposed hardware-efficient algorithm addresses the parking of a trailer (follower) robot in indoor environments by a truck (leader) robot with a rendezvous approach. In the process of parking, initial rendezvous behavioral control between the truck and trailer robots is established. Next, the parking space in the environment is estimated by the truck robot, and the trailer robot parks under the supervision of the truck robot. The proposed behavioral control mechanisms were executed between heterogenous-type computational-based robots. Optimized sensors were used for traversing and the execution of the parking methods. The truck robot leads, and the trailer robot mimics the actions in the execution of path planning and parking. The truck robot was integrated with FPGA (Xilinx Zynq XC7Z020-CLG484-1), and the trailer was integrated with Arduino UNO computing devices; this heterogenous modeling is adequate in the execution of trailer parking by a truck. The hardware schemes were developed using Verilog HDL for the FPGA (truck)-based robot and Python for the Arduino (trailer)-based robot. Full article

Fully autonomous trajectory planning for multiple unmanned aerial vehicles (UAVs) is significant for building the next generation of the logistics industry without human control. This paper presents a method to enable multiple UAVs to fly in the same trajectory without collision. It benefits several applications, such as smart cities and transfer goods, during the COVID-19 pandemic. Different types of nonlinear state estimation are deployed to test the position estimation of drones by treating the information from AirSim as offline dynamic data. The obtained global positioning system sensor data and magnetometer sensor data are determined as the measurement model. The experiment in the simulation is separated into (1) the localization state, (2) the rendezvous state, in which the proposed rendezvous strategy is presented by using the relation between velocity and displacement through the setting area, and (3) the full mission state, which combines both the localization and rendezvous states. The localization state results show the best RMSE in the case of full GPS available at 0.21477 m and 0.25842 m in the case of a GPS outage during a period of time by implementing the ensemble Kalman filter. Similarly, the ensemble Kalman filter performs well with an RMSE of 0.5112414 m in the rendezvous state and demonstrates exceptional performance in the full mission state. Moreover, the experiment is implemented in a real-world situation with some basic drone kits as proof that the proposed rendezvous strategy can truly operate. Full article

Deep space missions are recently gaining increasing interest from space agencies and industry, their maximum exponent being the establishment of a permanent station in cis-lunar orbit within this decade. To that end, autonomous rendezvous and docking in multi-body dynamical environments have been defined as crucial technologies to expand and maintain human space activities beyond near Earth orbit. Based on analytical and numerical formulations of the relative dynamics in the Circular Restricted Three Body Problem (CR3BP), a family of optimal, linear and nonlinear, continuous and impulsive, guidance and control techniques are developed for the design of end-to-end rendezvous trajectories between co-orbiting spacecraft in this multi-body dynamical environment. To this end, several modern control techniques are effectively designed and adapted to this problem, with particular emphasis on the design of low cost rendezvous manoeuvres. Finally, the designed hybrid rendezvous strategies, combining both discrete and continuous control techniques, are effectively tested and validated under several start-to-end deep space testbench mission scenarios, where their performance is compared and quantitatively assessed with a set of performance indices. Full article