Adaptive Hybrid Optimization Learning-Based Accurate Motion Planning of Multi-Joint Arm

Motion planning is important to the automatic operation of the manipulator. It is difficult for traditional motion planning algorithms to achieve efficient online motion planning in a rapidly changing environment and high-dimensional planning space. The neural motion planning (NMP) algorithm based on reinforcement learning provides a new way to solve the above-mentioned task. Aiming to overcome the difficulty of training the neural network in high-accuracy planning tasks, this article proposes to combine the artificial potential field (APF) method and reinforcement learning. The neural motion planner can avoid obstacles in a wide range; meanwhile, the APF method is exploited to adjust the partial position. Considering that the action space of the manipulator is high-dimensional and continuous, the soft-actor-critic (SAC) algorithm is adopted to train the neural motion planner. By training and testing with different accuracy values in a simulation engine, it is verified that, in the high-accuracy planning tasks, the success rate of the proposed hybrid method is better than using the two algorithms alone. Finally, the feasibility of directly transferring the learned neural network to the real manipulator is verified by a dynamic obstacle-avoidance task.

Point-to-point trajectory planning for space robots based on jerk constraints

This paper studies the Cartesian point-to-point optimal trajectory planning for space robots oriented to space maintenance operations. Aiming at the problems of poor stability, large base disturbance, and large joint variation in the motion planning of point-to-point maintenance in space, a planning method is proposed to minimize the base disturbance and the total joint angle variation under the jerk constraint on the premise of ensuring the accuracy of the end pose. First, the attitude of the space robot is described by the unit quaternion, and the velocity relationship between the joint angle, the end effector, and the base posture is introduced. Then, the joint trajectories were parameterized by a fifth degree polynomial, and a trajectory planning model with the minimum perturbation of the base and the minimum variation of the joint of the manipulator was established under the condition that the end effector satisfied the pose and the jerk constraint. Finally, a multi-objective optimization algorithm is proposed to deal with the trajectory optimization problem under nonlinear constraints. The simulation results show that the proposed trajectory planning method can optimize the base attitude and joint angle of the space manipulator under the premise of the optimal trajectory and stability of the terminal execution tool, which ensures the stability of the space robot's on-orbit service and reduces the energy consumption.

Robotic Manipulation and Capture in Space: A Survey

Space exploration and exploitation depend on the development of on-orbit robotic capabilities for tasks such as servicing of satellites, removing of orbital debris, or construction and maintenance of orbital assets. Manipulation and capture of objects on-orbit are key enablers for these capabilities. This survey addresses fundamental aspects of manipulation and capture, such as the dynamics of space manipulator systems (SMS), i.e., satellites equipped with manipulators, the contact dynamics between manipulator grippers/payloads and targets, and the methods for identifying properties of SMSs and their targets. Also, it presents recent work of sensing pose and system states, of motion planning for capturing a target, and of feedback control methods for SMS during motion or interaction tasks. Finally, the paper reviews major ground testing testbeds for capture operations, and several notable missions and technologies developed for capture of targets on-orbit.

Multitask-Based Trajectory Planning for Redundant Space Robotics Using Improved Genetic Algorithm

This work addresses the multitask-based trajectory-planning problem (MTTP) for space robotics, which is an emerging application of successively executing tasks in assembly of the International Space Station. The MTTP is transformed into a parameter-optimization problem, where piecewise continuous-sine functions are employed to depict the joint trajectories. An improved genetic algorithm (IGA) is developed to optimize the unknown parameters. In the IGA, each chromosome consists of three parts, namely the waypoint sequence, the sequence of the joint configurations, and a special value for the depiction of the joint trajectories. Numerical simulations, including comparisons with two other approaches, are developed to test IGA validity.

Assessment of ECG and respiration recordings from simulated emergency landings of ultra light aircraft

Pilots of ultra light aircraft have limited training resources, but with the use of low cost simulators it might be possible to train and test some parts of their training on the ground. The purpose of this paper is to examine possibility of stress inducement on a low cost flight simulator. Stress is assessed from electrocardiogram and respiration. Engine failure during flight served as a stress inducement stimuli. For one flight, pilots had access to an emergency navigation system. There were recorded some statistically significant changes in parameters regarding breathing frequency. Although no significant change was observed in ECG parameters, there appears to be an effect on respiration parameters. Physiological signals processed with analysis of variance suggest, that the moment of engine failure and approach for landing affected average breathing frequency. Presence of navigation interface does not appear to have a significant effect on pilots.

Equations of Motion of Free-Floating Spacecraft-Manipulator Systems: An Engineer's Tutorial

The paper provides a step-by-step tutorial on the Generalized Jacobian Matrix (GJM) approach for modeling and simulation of spacecraft-manipulator systems. The General Jacobian Matrix approach describes the motion of the end-effector of an underactuated manipulator system solely by the manipulator joint rotations, with the attitude and position of the base-spacecraft resulting from the manipulator motion. The coupling of the manipulator motion with the base-spacecraft are thus expressed in a generalized inertia matrix and a GJM. The focus of the paper lies on the complete analytic derivation of the generalized equations of motion of a free-floating spacecraft-manipulator system. This includes symbolic analytic expressions for all inertia property matrices of the system, including their time derivatives and joint-angle derivatives, as well as an expression for the generalized Jacobian of a generic point on any link of the spacecraft-manipulator system. The kinematics structure of the spacecraft-manipulator system is described both in terms of direction-cosine matrices and unit quaternions. An additional important contribution of this paper is to propose a new and more detailed definition for the modes of maneuvering of a spacecraft-manipulator. In particular, the two commonly used categories free-flying and free-floating are expanded by the introduction of five categories, namely floating, rotation-floating, rotation-flying, translation-flying, and flying. A fully-symbolic and a partially-symbolic option for the implementation of a numerical simulation model based on the proposed analytic approach are introduced and exemplary simulation results for a planar four-link spacecraft-manipulator system and a spatial six-link spacecraft manipulator system are presented.

Multi-objective pose optimal distribution method for the feed support system of Five-hundred-meter Aperture Spherical radio Telescope

The Five-hundred-meter Aperture Spherical radio Telescope is the world’s largest single-dish radio telescope and is located in the southwest of China. The cable-driven parallel robot and A-B rotator of the feed support system in Five-hundred-meter Aperture Spherical radio Telescope are designed to realize the theoretical position and attitude of the receiver. The feed support system is a pose-redundant and rigid–flexible coupling system; thus, the method of pose distribution between the A-B rotator and the cable-driven parallel robot impacts on the cable tension distribution and stiffness of the feed support system, which are crucial to the feed support system stability. The main purpose of this study is to examine the pose optimal distribution method for the feed support system. First, a mechanical model of the feed support system, which considers the time-varying barycenter of the feed cabin and the back-illuminated strategy of the receiver, is established. Then, a pose distribution method that ensures the position and attitude accuracy of the receiver is proposed for the feed support system. Considering the performance indices of the variance of cable tensions and the stiffness of the cable-driven parallel robot, an optimization of the rotation angles of the A-B rotator with multiple objectives is implemented using a genetic algorithm. Finally, simulations are conducted to demonstrate the effectiveness of the proposed method compared with others. Results show that the proposed approach not only ensures the attitude accuracy of the receiver but also maintains the lower variance of cable tensions and higher stiffness of the feed support system.

Repetitive Motion Planning of Free-Floating Space Manipulators

Abstract In this paper, a repetitive motion-planning scheme of free-floating space manipulators is presented. Repetitive motion means when one task ends, the end-effector pose, the joint angles and the base pose should reset (return to their initial value), which will facilitate the subsequent tasks. First, due to the lack of DOF, an order of priority to the given tasks is introduced. Second, the joint reset optimization operator, the base attitude reset optimization operator and the end-effector attitude reset optimization operator are designed. Then, the repetitive motion scheme is proposed by combining the three optimization operators above in a creative way. Finally, to make the optimization of repetitive motion obvious, the base attitude maintenance is also considered. Simulation results verify the correctness and the validity of the repetitive motion planning method of space manipulator.

Subsection Evolution in GA for Trajectory Planning of a Space Manipulator

Abstract A free-floating space manipulator has outstanding advantages and wide application prospects compared with other categories. This paper discusses the concepts and categories of space robots and introduces the current trajectory-planning algorithm for a space robot and its ground simulation system in the main countries of the world. This paper also constructs a system model for the space manipulator system and gives the kinematic equation of such a manipulator system. A dynamic equation of the manipulator's joints is also developed by using Lagrange equations. Continuous Cartesian trajectory planning is also studied in this paper based on differential kinematical equations and momentum conservation equations. Finally, this paper presents the subsection evolution algorithm in GA to realize the trajectory tracking of a free-floating space manipulator and a simulation about the free floating space manipulator and its corresponding analyses are given.

A Ground-Based Validation System of Teleoperation for a Space Robot

Teleoperation of space robots is very important for future on-orbit service. In order to assure the task is accomplished successfully, ground experiments are required to verify the function and validity of the teleoperation system before a space robot is launched. In this paper, a ground-based validation subsystem is developed as a part of a teleoperation system. The subsystem is mainly composed of four parts: the input verification module, the onboard verification module, the dynamic and image workstation, and the communication simulator. The input verification module, consisting of hardware and software of the master, is used to verify the input ability. The onboard verification module, consisting of the same hardware and software as the onboard processor, is used to verify the processor's computing ability and execution schedule. In addition, the dynamic and image workstation calculates the dynamic response of the space robot and target, and generates emulated camera images, including the hand-eye cameras, global-vision camera and rendezvous camera. The communication simulator provides fidelity communication conditions, i.e., time delays and communication bandwidth. Lastly, we integrated a teleoperation system and conducted many experiments on the system. Experiment results show that the ground system is very useful for verified teleoperation technology.

Autonomous target capturing of free-floating space robot: Theory and experiments

Space robotic systems are expected to play an increasingly important role in the future. Unlike on the earth, space operations require the ability to work in the unstructured environment. Some autonomous behaviors are necessary to perform complex and difficult tasks in space. This level of autonomy relies not only on vision, force, torque, and tactile sensors, but also the advanced planning and decision capabilities. In this paper, the authors study the autonomous target capturing from the issues of theory and experiments. Firstly, we deduce the kinematic and dynamic equations of space robotic system. Secondly, the visual measurement model of hand–eye camera is created, and the image processing algorithms to extract the target features are introduced. Thirdly, we propose an autonomous trajectory planning method, directly using the 2D image features. The method predicts the target motion, plans the end-effector's velocities and solves the inverse kinematic equations using practical approach to avoid the dynamic singularities. At last, numeric simulation and experiment results are given. The ground experiment system is set up based on the concept of dynamic simulation and kinematic equivalence. With the system, the experiments of autonomous capturing a target by a free-floating space robot, composed of a 6-DOF manipulator and a satellite as its base, are conducted, and the results validate the proposed algorithm.

The Cartesian Path Planning of Free-Floating Space Robot using Particle Swarm Optimization

The Cartesian path planning of free-floating space robot is much more complex than that of fixed-based manipulators, since the end-effector pose (position and orientation) is path dependent, and the position-level kinematic equations can not be used to determine the joint angles. In this paper, a method based on particle swarm optimization (PSO) is proposed to solve this problem. Firstly, we parameterize the joint trajectory using polynomial functions, and then normalize the parameterized trajectory. Secondly, the Cartesian path planning is transformed to an optimization problem by integrating the differential kinematic equations. The object function is defined according to the accuracy requirement, and it is the function of the parameters to be defined. Finally, we use the Particle Swarm Optimization (PSO) algorithm to search the unknown parameters. The approach has the following traits: 1) The limits on joint angles, rates and accelerations are included in the planning algorithm; 2) There exist not any kinematic and dynamic singularities, since only the direct kinematic equations are used; 3) The attitude singularities do not exist, for the orientation is represented by quaternion; 4) The optimization algorithm is not affected by the initial parameters. Simulation results verify the proposed method.