Attitude Constraints Research Articles

Cooperative digital magnetic‐elevation maps by small autonomous aerial robots

AbstractOne of the steps to provide fundamental data for planning a mining effort is the magnetic surveying of a target area, which is typically carried out by conventional aircraft campaigns. However, besides the high cost, fixed‐wing aerial vehicles present shortcomings especially for drape flights on mountainous regions, where steep slopes are often present. Traditional human‐crewed flights have to perform tedious and dangerous trajectories, under strict velocity and attitude constraints. In this paper, we deal with the problem of accomplishing digital magnetic‐elevation maps using autonomous and cooperative aerial robots. The proposed approach for autonomous mapping utilizes a custom‐built fluxgate sensor and off the shelf cameras adapted for small airborne platforms. We also propose an innovative approach for generating a digital magnetic‐elevation model from the gathered data. Our method was evaluated and validated in field tests in an industrial scenario to detect scrap metals in ore piles. Results show that the proposed method could reliably detect magnetic anomalies while generating accurate three‐dimensional magnetic maps.

A study on large parts precision docking method based on 6-axis industrial robot

In view of the docking assembly difficulties of spacecraft large parts, resulting from the irregular contour and the inadequacy of process clamping points, this paper puts forward a method fitting the attitude relations of the docking parts based on the coordinates of the feature points, obtaining the target attitude of the docking parts based on the process constraints, and controlling 6-axis industrial robot achieves precise docking of large parts. Firstly, the composition of the large parts docking system is introduced, and the docking model is described by the selection of the measurement feature points and the establishment of the coordinate system. After that, a docking control algorithm based on the attitude constraints of large parts is established. Finally, In the RobotStudio and Matlab co-simulation environment, the attitude adjustment process of the large parts is simulated. The simulation results show that this study provides an effective method for precision docking of spacecraft engine large parts based on feature points, which is completed by 6-axis industrial robot.

A novel guaranteed tracking performance control for reentry vehicle with actuator constraints and uncertainties

A novel guaranteed tracking performance control scheme is presented for the reentry vehicle encountered in actuator saturation and enormous amount of uncertainties via time-varying barrier Lyapunov function (TVBLF) method. The required stable and transient tracking performance of the reentry attitudes are simultaneously enhanced by the proposed logarithm-type TVBLF and the control design complexity is reduced compared with the prescribed performance technique. Moreover, in order to eliminate the control performance degradation caused by the actuator constraints, an auxiliary error compensation design is inserted into the control law. In addition, the uncertainty rejection capability of the control system is achieved by exploiting the MIMO nonlinear extended disturbance observer. Finally, the uniform ultimately boundedness of the closed-loop system is established and numerical simulations are verified to demonstrate the effectiveness of the proposed control law for the reentry vehicle subject to attitude constraints, actuator saturations and uncertainties.

Quadrotor trajectory generation and tracking for aggressive maneuvers with attitude constraints

Abstract This paper addresses the problem of performing quadrotor aggressive maneuvers that are attitude-constrained. The trajectory generation is formulated as a quadratic programming problem with linear constraints. Constraints at a specific time can be imposed on any linear combination of the quadrotor position and its derivatives. The under-actuation of the vehicle is explored to embed the attitude constraints into the trajectory generation via constraints on the desired quadrotor acceleration. A trajectory tracking controller is also proposed that guarantees the asymptotic stability of the closed-loop tracking system. Experimental and simulation results illustrate the application of the proposed method to quadrotor maneuvers involving a 360° flip.

Energy-optimal spacecraft attitude maneuver path-planning under complex constraints

The objective of this study is an energy-optimal attitude maneuver path for rigid body spacecraft under complex constraints. Complex attitude constraints are first established; the attitude pointing constraints are written in non-convex quadratic form. The constrained attitude maneuver problem is then formulated as the non-convex quadratically constrained quadratic programming problem which targets the minimal energy-cost. An improved differential evolution algorithm is then built which utilizes the standard DE algorithm from the F value of the mutation operator and the crossover operator CR value to enhance the mutation strategy and ultimately obtain a near-optimized solution to the problem. Simulation results show that this method not only satisfies the complex attitude constraints, but also reveals the optimal path for global attitude optimization. It also consumes relatively little energy with remarkable efficiency.

Distributed Attitude Coordinated Control of Multiple Spacecraft With Attitude Constraints

This paper addresses the distributed attitude coordinated tracking problem for multiple constrained spacecraft by state and output feedback. Since only parts of the followers can acquire the states of the dynamic leader, a distributed finite-time sliding-mode estimator is first proposed to reconstruct the information of the leader's attitude and angular velocity accurately. Then, to guarantee the attitude constraints of spacecraft systems, we use the integral barrier Lyapunov function technique to propose a distributed state feedback attitude tracking control algorithm. Next, in the case without angular velocity sensors, we design a distributed attitude tracking control law via output feedback using high-gain observers. In the two proposed control schemes, the adaptive neural networks are introduced to tackle the model uncertainties. The uniform ultimate boundedness of all the state errors can be guaranteed by the Lyapunov stability theory. Finally, numerical results are given to show the feasibility of the proposed schemes.

Deep learning based trajectory optimization for UAV aerial refueling docking under bow wave

In the autonomous aerial refueling (AAR) docking process, the bow wave generated by the receiver has a strong effect on the drogue, which affects the docking success rate greatly. Thus, a deep learning based trajectory optimization method which aims to decrease the bow wave effect on the drogue is proposed in this paper. There are mainly three parts in the proposed trajectory optimization method. Firstly, a precise bow wave model based on deep learning is presented to estimate the bow wave effect on the drogue. Furthermore, due to the dynamic characteristic of the drogue, a simple and practical drogue motion prediction model under multiple disturbances is carried out to provide a precise prediction of the drogue position at the next time. Moreover, considering the strict attitude constraints requirements in the AAR docking process, a novel reference observer is designed to estimate the receiver attitude from the optimized trajectory under wind perturbations. Then, the proposed trajectory optimization method could not only diminish the bow wave effect on the drogue largely but also satisfy the attitude constraints of the receiver. Finally, the effectiveness of the proposed method is demonstrated by the simulations.

Search-Based Motion Planning for Aggressive Flight in SE(3)

Quadrotors with large thrust-to-weight ratios are able to track aggressive trajectories with sharp turns and high accelerations. In this letter, we develop a search-based trajectory planning algorithm that exploits the quadrotor maneuverability to generate sequences of motion primitives in cluttered environments. We model the quadrotor body as an ellipsoid and compute its flight attitude along trajectories in order to check for collisions against obstacles. The ellipsoid model allows the quadrotor to pass through gaps that are smaller than its diameter with nonzero pitch or roll angles. Without any prior information about the location of gaps and associated attitude constraints, our algorithm is able to find a safe and optimal trajectory that guides the robot to its goal as fast as possible. To accelerate planning, we first perform a lower dimensional search and use it as a heuristic to guide the generation of a final dynamically feasible trajectory. We analyze critical discretization parameters of motion primitive planning and demonstrate the feasibility of the generated trajectories in various simulations and real-world experiments.

Optimal formation reconfiguration of satellites under attitude constraints using only thrusters

An optimal formation reconfiguration method under the constraints of a satellite attitude with respect to an inertial frame is addressed. Both the satellite position and attitude are controlled by only two body-fixed thrusters for an in-plane maneuver. To tackle the underactuated control problem, an attitude controller for tracking reference accelerations is firstly derived on the basis of Lyapunov approach. This controller allows us to consider the attitude constraints as input directional constraints because the satellite attitude is controlled so that the thrust direction is coincide with the force direction required for the orbit transfer. Secondly, a formation reconfiguration method based on the Fourier series is used as the reference inputs, and boundary conditions that make the resulting input trajectory an ellipse are shown. Such elliptic input trajectory changes the input direction monotonically, which enables bounding it around an desired direction. The proposed underactuated-controller achieves a reconfiguration maneuver while keeping the satellite attitude within a range from a specified direction, and thus is useful when several thrusters of a satellite fail due to malfunctions. Finally, numerical simulation results validate the effectiveness of the proposed relocation method by comparing energy consumptions and bounded satellite attitude angles.

Integrated distributed formation flight control with aerodynamic constraints on attitude and control surfaces

This paper investigates a 3-D leader-following formation control problem for a group of missiles with aerodynamic constraints. To cope with the large maneuvering formation flight in bank-to-turn control mode, an integrated backstepping-based distributed control scheme, combining the inner-loop attitude manipulation and outer-loop formation control, is proposed. Command filters are introduced to handle the control surface saturations caused by the physical limitations, and the attitude constraints derived from the coordinated turn requirements. In addition, the B-spline neural networks are adopted to reconstruct the uncertain aerodynamic force and moment coefficients, of which the unknown parameters are then online learned by the adaptive tuning laws. The proposed integrated distributed formation control protocol will guarantee that all states in the closed-loop systems are cooperatively semi-globally uniformly ultimately bounded. The formation tracking errors can converge into a small region around zero by properly adjusting the control parameters. Finally, numerical simulations are conducted to demonstrate the effectiveness of the proposed control scheme.

Intelligent attitude planning algorithm based on the characteristics of low radar cross section characteristics of microsatellites under complex constraints

The attitude optimization problem of spacecraft under restricted conditions is an important issue of spacecraft planning control. This paper aims at on-orbit microsatellites, which is based on the directional characteristics of their own low radar cross section designs, maintaining low detection probabilities for ground, sea, and space-based detection systems, and simultaneously satisfying the constraint conditions of complex attitude constraints. In this paper, an improved pigeon-inspired optimization algorithm and a nonredundant attitude description method—modified Rodrigues parameters—are used to solve the problem of attitude optimal planning for satellites under complex constraints. This paper focuses on the core evolution mathematical model of the pigeon-inspired optimization algorithm based on the modified Rodrigues parameter, the iterative evolution process of the individual in the pigeon population, and the fitness function model of the individual at different positions. The comparison between the classical pigeon-inspired optimization algorithm and the improved pigeon-inspired optimization algorithm is made in the planned result and resource occupancy, respectively. The simulation results show that the improved algorithm has a faster convergence speed and a smoother optimization result than the classic pigeon-inspired optimization algorithm, where it greatly reduces the computational load and reduces the load of the control system, thus achieving an optimal algorithm.

Communication in palliative care: the applicability of the SAGE and THYME model in Singapore.

Majority of the progress and development in palliative care in the last decade has been improvements in physical aspects of treatment, namely pain and symptom management. Psychosocial aspects of care have improved, although not enough to meet the needs of many patients and family members. This is evident in many parts of the world and notably in Singapore, where palliative care is seen as an emerging medical and nursing specialty. To discuss the implementation of the SAGE and THYME communication model in a palliative care context. The article examines the use of the model and how its implementation can improve communication between patients and nurses. The model works by reviewing contemporary developments made in relation to improving communication in palliative care. These include, highlighting the importance of meeting individual needs, therapeutic relationship building, and advanced communication training within a Singaporean context. The implementation of the SAGE and THYME model can be a useful way of enabling nurses to improve and maintain effective communication in a medically dominated health care system. The challenges and constraints in educating and training nurses with limited skills in palliative care, forms part of the review, including the cultural and attitude constraints specific to Singaporean palliative care.

Intelligent landing strategy for the small bodies: from passive bounce to active trajectory control

Landing exploration is an important way to improve the understanding of small bodies. Considering the weak gravity field as well as the strict attitude constraints which make bounce a common situation and a tough issue for safe landing on small bodies, a novel active trajectory control-based intelligent landing strategy is proposed to improve the safety and reliability of mission. The scenarios of intelligent landing strategy for both safe landing and hopping exploration are introduced in detail and a potential structure for autonomous navigation and control system is presented. Furthermore, a convex optimization-based control algorithm is developed, which is the key technology fulfilling the active trajectory control. Meanwhile a novel discretization method based on the fourth-order Runge-Kutta rule is proposed to improve the accuracy. A helpful adjustment process of time-to-landing is also introduced when the feasible trajectory does not exist. Comprehensive simulations about the proposed intelligent landing strategy are performed to demonstrate the improved safety and accuracy of both landing and hopping exploration on small bodies. Meanwhile, the performance and accuracy of the proposed convex optimization-based control algorithms is also compared and discussed thoroughly. Some useful conclusions for control system design are also obtained.

Minimum-Time Reconfiguration Maneuvers of Satellite Formations Using Perturbation Forces

A novel approach for minimum-time reconfiguration of satellite formations is proposed considering the perturbation forces as control variables. Planning appropriate attitude maneuvers for each satellite, the atmospheric drag and of the solar radiation pressure are properly controlled, and the formation is given the appropriate inputs to achieve the imposed reconfiguration. Limits and advantages of the presented maneuvers are examined considering low Earth orbits, medium Earth orbits, and geostationary orbits. The recent inverse dynamics particle swarm optimization is involved; the integration of the attitude dynamics is avoided, thus reducing the computational effort, and satisfied attitude constraints at the initial and final time instants are guaranteed. B-spline curves approximate the attitude kinematics, variable time mesh points are introduced, and adaptive decreasing tolerances are considered for the imposed constraints. The evolution of the configuration is simulated with a high-fidelity orbital simulator considering all the perturbations that can affect the maneuver. Two test cases are taken into account, one involving a circular formation reconfiguration and the other an along-track reconfiguration.

Fast Autonomous Three-Axis Constrained Attitude Pathfinding and Visualization for Boresight Alignment

A new algorithm suitable for fast onboard implementation is presented for designing attitude maneuver paths that achieve desired boresight alignment in the presence of multiple three-axis attitude constraints. It is based on a recently proposed algorithm in which possible attitudes are discretized in a three-dimensional distortion-minimizing projected space. In that space, grid points are enumerated and graph search pathfinding algorithms are employed to find the shortest constrained path between selected initial and target grid points. The new algorithm extends this approach from a single target point to a continuum of target points, representing all possible attitudes that maintain the desired boresight alignment. It augments the original algorithm with the transformation that makes it possible to assign a single value to estimated distances for the whole continuum of target points. This, in turn, allows the pathfinding algorithms to efficiently determine the shortest overall path to the whole continuum, which corresponds to the shortest attitude maneuver path that achieves the desired boresight alignment.

Invariant set based sliding mode control for near-space vehicles with attitude constraints

In this article, a robust attitude control scheme, which is called sliding mode control with unidirectional auxiliary surfaces (UAS-SMC), is proposed for the near-space vehicle with attitude constraints and time-varying unknown disturbance. Firstly, the positively invariant sets are designed with the UAS-SMC method. The invariant property of these sets can be utilized to guarantee the attitude constraints. Secondly, a UAS nonlinear disturbance observer is firstly developed for the NSV with time-varying unknown disturbance. By introducing the information of UAS surfaces, the performance of this observer is enhanced. The convergence of all closed-loop signals is rigorously proved via Lyapunov analysis method under the developed robust UAS-SMC scheme. Finally, simulation results are given to illustrate the effectiveness of the proposed attitude control scheme.

Fast Three-Axis Constrained Attitude Pathfinding and Visualization Using Minimum Distortion Parameterizations

A new algorithm for designing attitude maneuver paths in the presence of multiple three-axis attitude constraints is presented. The algorithm projects the full three-axis attitude representation into a three-dimensional space using a new distortion-minimizing transformation. The projected representation is discretized on a three-dimensional Cartesian grid and the admissible regions emerge in the projected space from the discretized representation via interpolation of the constraint satisfaction across the grid points. The points are enumerated and graph search algorithms are employed to find minimum cost paths using the appropriately selected cost definitions. The paths are then smoothed and visualized alongside with the admissible regions in three dimensions. Ultimately, the paths can serve as targets for attitude tracking control algorithms.

Path Planning of Spatial Rigid Motion with Constrained Attitude

This paper presents a general quadratic optimization methodology for autonomous path planning of spatial rigid motion with constrained attitude. The motion to be planned has six degrees of freedom and is assumed under constant velocity in the body frame. The objective is to determine the motion orientation (or attitude), handled as control variables, along the planned paths. A procedure is discussed to transform the rotational constraints and attitude constraints as quadratic functions in terms of unit quaternions, and the path-planning problem is reformulated as a general, quadratically constrained, quadratic programming problem. A semidefinite relaxation method is then applied to obtain a bound on the global optimal value of the nonconvex, quadratically constrained, quadratic programming problem. Subsequently, an iterative rank minimization approach is proposed to find the optimal solution. Application examples of aircraft path-planning problems are presented using the proposed method and compared with those obtained from the other method.

Robust Adaptive Attitude Control for Airbreathing Hypersonic Vehicle with Attitude Constraints and Propulsive Disturbance

A robust adaptive backstepping attitude control scheme, combined with invariant-set-based sliding mode control and fast-nonlinear disturbance observer, is proposed for the airbreathing hypersonic vehicle with attitude constraints and propulsive disturbance. Based on the positive invariant set and backstepping method, an innovative sliding surface is firstly developed for the attitude constraints. And the propulsive disturbance of airbreathing hypersonic vehicle is described as a differential equation which is motivated by attitude angles in this paper. Then, an adaptive fast-nonlinear disturbance observer for the proposed sliding surface is designed to estimate this kind of disturbance. The convergence of all closed-loop signals is rigorously proved via Lyapunov analysis method under the developed robust attitude control scheme. Finally, simulation results are given to illustrate the effectiveness of the proposed attitude control scheme.

Omnidirectional Analysis of Spatial Manipulator

Space manipulators are mainly used in the spatial loading task. According to problems of the spatial loading diversity, the testing loading installing position, and the utilization ratio of a test platform, the space manipulator is asked to evaluate the position and attitude of itself. This paper proposes the Point Omnidirectional Coefficient (POC) with unit attitude sphere/circle to describe attitude of the end-effector, which evaluates any points in the attainable space of the manipulators, in combination with the manipulation’s position message, and get relationships between its position and attitude of all points in the attainable space. It represents the mapping between sphere surface and plane for mission attitude constraints and the method for calculating volume of points space including attainable space, Omnidirectional space, and mission attitude space. Furthermore, the Manipulator Omnidirectional Coefficient based on mission or not is proposed for evaluating manipulator performance. Through analysis and simulation about 3D and 2D manipulators, the results show that the above theoretical approach is feasible and the relationships about link lengths, joints angles, attainable space, and Manipulator Omnidirectional Coefficient are drawn for guiding design.