Houde Liu

Modeling and simulation of space robot visual servoing for autonomous target capturing

In the past decades, autonomous on-orbit servicing has become a priority for the space industry. Visual servo of eye-in-hand type system is one of the most promising approaches to perform this task. In order to ensure that the task was implemented successfully, mathematical simulation and ground experiments are required to thoroughly explore the capabilities and limitations of the planning and control algorithms before it is launched. In this paper, we propose a hybrid 2D/3D visual servoing of space robot for target capturing. We consider the image based visual servo as the core of our scheme due to its simplicity and low sensitivity to camera calibration errors. Position based visual servoing is only used when the target is close to the end effector of space robot. Taking account of the special aspects of space environment such as lighting and available computing power, to realize a safe and reliable realtime visual servoing operation, cooperative visual marker, time delay processing, and capture strategy have been carefully designed. A 3D simulation platform for space robot visual servoing is developed to verify the corresponding algorithms. The results validate the effectiveness of our research.

Robust state estimation and fault detection combining unknown input observer and set-membership approach

This paper aims to propose a new robust state-estimation and fault-detection method by combining the unknown input observer (UIO) and the set-membership estimator (SME). It is known that both the SUIO and the SME can be used to estimate the states of a system. The former aims to obtain a particular value by actively decoupling the effect of unknown inputs, while the latter can obtain state-estimation sets by prediction and correction based on the set theory. Instead of particular state values, the latter can obtain state-estimation sets guaranteeing to contain system states (i.e., robust state estimation). In this paper, we propose to use the framework of the UIO to actively decouple part of unknown inputs and then further employ the set-membership estimation method to estimate state sets and detect faults. The objective of the proposed method is to reduce the conservatism of robust state-estimation sets by using the UIO to remove the contribution of part of unknown inputs to the sizes of state-estimation sets. At the end of this paper, a numerical example is used to illustrate the effectiveness and advantages of the proposed approach.

Vibration suppression of a large flexible spacecraft for on-orbit operation

Flexible appendages, such as solar panels, communication antennas and other large structures, are mounted on the base of a space robot and target satellite. The vibration of the flexible structure is excited by operations of a space manipulator. It is very challenging to control the vibration of large flexible appendages for on-orbit operation and, especially when the manipulator operates a non-cooperative target with unknown structural parameters and vibration information. In this study, a hybrid control method is proposed based on wave-based control and PD control methods to control the motion of a manipulator while suppressing the vibration of appendages. First, the rigid-flexible coupled dynamic model of a compounded system is established. This is followed by designing a hybrid control strategy combining wave-based control and PD control for rest-to-rest maneuvers based on the characteristics of the compounded system. Finally, the simulation of a 3D compounded system is provided to verify the effectiveness of the presented approach. The simulation results indicate that the space robot can successfully berth the target while suppressing the vibrations of the structure.

Autonomous path planning and experiment study of free-floating space robot for spinning satellite capturing

Robotic systems are expected to play an increasingly important role in future space activities with the development of space technology. The robotic on-orbital service, whose key is the capturing technology, becomes research hot in recent years. This paper focuses on the guidance of a robot manipulator to capture a spinning satellite with unknown dynamics parameters. In capturing a spinning satellite, a reference trajectory for control of the manipulator is generated with time delay due to the processing time of the target motion estimator and the manipulator controller. Consequently, the control system shows a poor performance and the end-effector sometimes fails to capture the target satellite. To solve this problem, the motion characteristics and motion prediction of the spinning satellite is analyzed Firstly, and using Unscented Kaiman Filter (UKF) to predict its movement. Then, a method of autonomous path planning of a free-floating space robot for target capturing is proposed, which is based on motion prediction and speed compensation. Finally, a ground experiment system is set up based on the concept of dynamic emulation and kinematic equivalence. With the experiment system, the autonomous target capturing experiments are conducted. The experiment results validate the proposed algorithm.

On the autonomous target capturing of flexible-base space robotic system

Autonomous target capturing is the key for space robot to perform on-orbital servicing tasks. To meet the requirement of complex and long-term task, large flexible appendages, such as solar paddles and antenna reflectors are usually mounted on the base of a space robot. Due to the structure vibration, it is very challenging to capture a free-floating target satellite. In this paper, we derived the kinematics equations and proposed the autonomous target capturing method for free-floating flexible-base space robots. The kinematics equation established the mapping from the base velocities, joint rates and elastic motion to the end-effector velocities. Based on this equation, we designed resolved motion rate control with vibration compensation for the space manipulator. Another contribution of this paper is that we modeled the dynamic coupling between the rigid movement of the end-effector and the flexible vibration of the solar paddles. Based on this model, we analyzed the coupling effect which was very important for the design of the manipulator and determining the trajectory planning and control strategy. At last, a simulation system was created and simulation studies of the proposed methods were carried out. The simulation results verify the proposed methods.

BRoPH: An efficient and compact binary descriptor for 3D point clouds

Abstract 3D feature descriptor plays an essential role in 3D computer vision as it is a pre-requisite step for many 3D vision applications. Despite there exists many 3D feature descriptors currently, they are mostly represented in floating representation, resulting costly computation and storage. In this paper, we propose a 3D binary local feature descriptor, Binary Rotational Projection Histogram (BRoPH), aimed at compactness of representation and efficiency of computation. BRoPH is generated directly from point cloud by turning the description of 3D point cloud into a series binarization of 2D image patches. The exploited local reference frame promotes the construction efficiency meanwhile maintains repeatability and stability, the multi-view mechanism and integration of density distribution and depth information employed in BRoPH complement each other and enhance its descriptiveness, and the multi-scale extension of Center-Symmetric Local Binary Patterns (CS-LBP) provides an efficient and compact way to generate binary string. We compare BRoPH against several representative descriptors on public datasets and demonstrate that it achieves about 14 times more compact, 28 and 4 times more faster in terms of describing and matching time respectively, than the average performance of the compared floating descriptors.

A particle filter and long short term memory fusion algorithm for failure prognostic of proton exchange membrane fuel cells

Prognostics and Health Management (PHM) appears to be a promising maintenance strategy which can enhance reliability and reduce maintenance costs of the target system. In the process of PHM, Prognostics is the most important and crucial. Prognostic approaches can be roughly divided into two categories: model-based methods and data-driven methods, both of which have advantages and limitations. To overcome the limitations of these methods and improve the accuracy and precision of the forecasting, we propose a novel fusion prognostic method. This method fuses the Particle Filter (PF, model-based) and Long Short Term Memory (LSTM, data-driven) algorithms. In the literature, PF is used by estimating the system state and identifying the parameters of the model for the purpose of Prognostic. However, it does not have ideal performance due to the lack of measurements in the prediction phase. To solve this problem, LSTM is used to forecast the measurements and use the results as the observation of PF. The experiment is applied to the data of Proton Exchange Membrane Fuel Cell Stack from IEEE PHM 2014 Data Challenge. The results demonstrate that the proposed method can effectively integrate the advantages of PF and LSTM, which leads to a better forecasting performance than naive PF approach.

Dynamic coupling of space robots with flexible appendages

For a space robot with flexible appendages, the structure flexibilities will easily cause vibration during orbit and/or attitude maneuver of the base, and the operation of the manipulators. Hence, the pose (position and attitude) of the end-effector will deviate from the desired values largely. In this paper, we derive the rigid-flexible coupling dynamics of a space robot system with flexible appendages and establish the coupling model between the flexible structure and the space manipulator. Then, some coupling factors are defined to measure the coupling degree between the flexible motion of the appendages and the rigid motion of the end-effector. Moreover, a new type of coupling map is proposed and drawn in joint space to represent the coupling motion between the joint and the appendages. The coupling map is very important for trajectory planning to reduce appendage vibration. The above work supplies a theoretic basis to guide the system design, performance evaluation, trajectory planning and motion control of such space robots.

A Fast Weighted Registration Method of 3D Point Cloud Based on Curvature Feature

In order to realize the fast and accurate registration of 3D point cloud data, a new fast weighted registration method is proposed in this paper. Firstly, using curvature feature, the method samples the original 3D point cloud data to quickly find matching points and remove wrong point pairs. Secondly, by introducing the iterative re-weighted least squares (IRLS) algorithm, the method carries out coarse alignment of the scattered point cloud. Finally, the method presents an improved distance-weighted Iterative Closest Point (ICP) algorithm to achieve fine matching. The experimental results show that the method has good convergence, robustness and accuracy.

Extension of virtual decomposition control to cooperative carrying of dual-arm robots in free motion

This investigation is to deal with the internal force control issue for cooperative carrying of dual-arm robots in free motion using virtual decomposition control. According to the virtual decomposition control principle, the entire system of the dual-arm robot in free motion for cooperative carrying is virtually decomposed into two chain subsystems and an object subsystem. The motion control problem of this entire system is converted into that of subsystems in which the internal force control of the object is performed. On the basis of establishing the mathematical model of the entire system, kinematics and dynamics of every subsystem are calculated. A virtual decomposition controller of each subsystem is designed, and this controller and the corresponding subsystem structure a control subsystem of this robot. All subsystem controllers constitute the controller of the entire robot system, and the combination of this controller and the robot system is the virtual decomposition control system of this robot. Stability analysis of the devised robot virtual decomposition control system is accomplished analyzing the virtual stability of each control subsystem by way of the virtual power flow related to the products of velocities errors and force errors. Finally, the virtual decomposition control system of the dual-arm robot to carry an object in free motion is simulated. Simulation results show that the virtual decomposition control system is stable and effective.