Explicit dynamics of space free-flyers with multiple manipulators via SPACEMAPLE

This paper focuses on the dynamics of a multiple manipulator space free-flying robot (SFFR) with rigid links and issues relevant to the development of appropriate control algorithms. To develop an explicit dynamics model of such complex systems, the Lagrangian formulation is applied. First, the system kinetic energy is derived based on a developed kinematics approach. Then, through vigorous mathematical analyses, three formats are obtained which describe the contribution of each term of kinetic energy to the equations of motion. Next, explicit derivations of a system's mass matrix, and of the vectors of non-linear velocity terms and generalized forces are introduced for the first time. The obtained dynamics model is very useful for dynamics analyses, design and development of control algorithms for such complex systems. The explicit SFFR dynamics can be implemented either numerically or symbolically. Following the latter approach, the developed symbolic code for dynamics modeling, i.e. SPACEMAPLE, and its verification procedure are described, and issues relevant to the development and computation of dynamics models in control algorithms are briefly discussed. Specific dynamic characteristics of SFFRs compared to fixed-base manipulators are pointed out.     

A non-linear model of shape and motion for tracking finger spelt American sign language

This work presents a piecewise linear approximation to non-linear Point Distribution Models for modelling the human hand. The work utilises the natural segmentation of shape space, inherent to the technique, to apply temporal constraints, which can be used with CONDENSATION to support multiple hypotheses and discontinuous jumps within shape space. This paper presents a novel method by which the one-state transitions of the English Language are projected into shape space for tracking and model prediction using an HMM like approach. The paper demonstrates that this model of motion provides superior results to that of other tracking approaches.     

Sweep scan path planning for efficient freeform surface inspection on five-axis CMM

Compared with the traditional 3-axis coordinate measuring machine (CMM), a 5-axis CMM equipped with the capability of continues sweep scanning can provide much denser data points while taking much shorter time. This paper presents an automatic sweep scan path planning system that generates a continuous sweep scanning path for the inspection of an arbitrary free-form surface using a 5-axis CMM with three translational axes and a rotary head with two very light rotary axes. The system strives to significantly improve the scanning efficiency by utilizing the superb kinematic advantages of the two rotary axes, which have very low moment of inertia, to cover a larger area, while tremendously reducing the speed and acceleration demand on the three translational axes which have much larger inertia. The path is generated from a mesh model of the freeform surface and an iterative approach is used to ensure that the stylus contacts the surface at an acceptable angle during the entire scan. Physical scanning experiments are performed and the test results show significant improvement in scanning efficiency by the proposed sweep scan path planning method when compared with some existing continuous scanning path planning approaches such as the standard isoparametric or zigzag method.     

Roadmap-based motion planning in dynamic environments

In this paper, a new method is presented for motion planning in dynamic environments, that is, finding a trajectory for a robot in a scene consisting of both static and dynamic, moving obstacles. We propose a practical algorithm based on a roadmap that is created for the static part of the scene. On this roadmap, an approximately time-optimal trajectory from a start to a goal configuration is computed, such that the robot does not collide with any moving obstacle. The trajectory is found by performing a two-level search for a shortest path. On the local level, trajectories on single edges of the roadmap are found using a depth-first search on an implicit grid in state-time space. On the global level, these local trajectories are coordinated using an A/sup */-search to find a global trajectory to the goal configuration. The approach is applicable to any robot type in configuration spaces with any dimension, and the motions of the dynamic obstacles are unconstrained, as long as they are known beforehand. The approach has been implemented for both free-flying and articulated robots in three-dimensional workspaces, and it has been applied to multirobot motion planning, as well. Experiments show that the method achieves interactive performance in complex environments.     

Estimating the non-linear dynamics of free-flying objects

This paper develops a model-free method to estimate the dynamics of free-flying objects. We take a realistic perspective to the problem and investigate tracking accurately and very rapidly the trajectory and orientation of an object so as to catch it in flight. We consider the dynamics of complex objects where the grasping point is not located at the center of mass.To achieve this, a density estimate of the translational and rotational velocity is built based on the trajectories of various examples. We contrast the performance of six non-linear regression methods (Support Vector Regression (SVR) with Radial Basis Function (RBF) kernel, SVR with polynomial kernel, Gaussian Mixture Regression (GMR), Echo State Network (ESN), Genetic Programming (GP) and Locally Weighted Projection Regression (LWPR)) in terms of precision of recall, computational cost and sensitivity to choice of hyper-parameters. We validate the approach for real-time motion tracking of 5 daily life objects with complex dynamics (a ball, a fully-filled bottle, a half-filled bottle, a hammer and a pingpong racket). To enable real-time tracking, the estimated model of the object’s dynamics is coupled with an Extended Kalman Filter for robustness against noisy sensing.     

基于虚拟样机技术的空间机器人系统的建模与仿真

首次采用虚拟样机技术对空间机器人系统进行建模和仿真,得出了反映机器人与卫星本体间运动学和动力学耦合情况的一些重要结果、为保持本体姿态稳定和驱动机器人按预定轨迹运动所需的控制力矩等．该方法可方便地用于验证固定基座、自由飞行、自由飘浮机器人的路径规划、控制算法、奇异空间等．与其它建模和仿真方法相比,该方法建模简单、可视化强、后处理功能极其强大,可实现多刚体系统闭环控制的仿真．     

Invariant surface and motion estimation from sparse range data

In this paper, we present a system for the estimation of the surface structure and the motion parameters of a free-flying object in a tele-robotics experiment. The system consists of two main components: (i) a vision-based invariant-surface and motion estimator and (ii) a Kalman filter state estimator. We present a new algorithm for motion estimation from sparse multi-sensor range data. The motion estimates from the vision-based estimator are input to a Kalman filter state estimator for continuously tracking a free-flying object in space under zero-gravity conditions. The predicted position and orientation parameters are then fed back to the vision module of the system and serve as an initial guess in the search for optimal motion parameters. The task of the vision module is two-fold: (i) estimating a piecewise-smooth surface from a single frame of multi-sensor data and (ii) determining the most likely (in the Bayesian sense) object motion that makes data in subsequent time frames to have been sampled from the same piecewise-smooth surface. With each incoming data frame, the piecewise-smooth surface is incrementally refined. The problem is formulated as an energy minimization and solved numerically resulting in a surface estimate invariant to 3D rigid motion and the vector of motion parameters. Performance of the system is depicted on simulated and real range data.     

基于线性规划的碰撞检测算法研究

介绍了虚拟环境中一种基于凸多面体面信息对偶线性规划模型(DualModel)的快速旋转和移动物体之间干涉碰撞实时检测方法。该文详细介绍了建模过程和求解步骤,物体由构成凸多面体的三角形面信息表示,而物体的运动由一组虚拟现实环境中的全局移动和旋转矩阵表示。这种数学编程方法具有数据结构简单、算法可靠和速度快等优点,同时能够很好地解决高速(运动帧)碰撞的问题。这一方法通过使用主-对偶(primal-dual)内点方法来解线性规划方程,具有很好的效果,能够检测多物体对之间的碰撞。实验结果表明,基于数学编程的方法相对两种著名的工具包I-COLLIDE和SOLID,具有速度快和稳定可靠的优点,而I-COLLIDE和SOLID工具包基于两种著名的算法:LinCanny(LC)最近特征算法和GJK算法(EnhancedGilbertJohnsonandKeethialgorithm)。     

Extending obstacle avoidance methods through multiple parameter-space transformations

Obstacle avoidance methods approach the problem of mobile robot autonomous navigation by steering the robot in real-time according to the most recent sensor readings, being suitable to dynamic or unknown environments. However, real-time performance is commonly gained by ignoring the robot shape and some or all of its kinematic restrictions which may lead to poor navigation performance in many practical situations. In this paper we propose a framework where a kinematically constrained and any-shape robot is transformed in real-time into a free-flying point in a new space where well-known obstacle avoidance methods are applicable. Our contribution with this framework is twofold: the definition of generalized space transformations that cover most of the existing transformational approaches, and a reactive navigation system where multiple transformations can be applied concurrently in order to optimize robot motion decisions. As a result, these transformations allow existing obstacle avoidance methods to perform better detection of the surrounding free-space, through “sampling” the space with paths compatible with the robot kinematics. We illustrate how to design these space transformations with some examples from our experience with real robots navigating in indoor, cluttered, and dynamic scenarios. Also, we provide experimental results that demonstrate the advantages of our approach over previous methods when facing similar situations.

On repelling robotic trajectories: coordination in navigation of multiple mobile robots

The paper attacks the problem of motion planning of a set of mobile robots. While artificial potential fields are the simplest methods of use, they are also locally optimal and can be easily stuck in scenarios. Probabilistic roadmap, elastic roadmaps, elastic strip and similar methods have a weak modelling of coordination between the robots. An inspiration is drawn from the artificial potential field method where the potential is computed in configuration space. In this paper the notion is extended to a ‘trajectory space’, where the complete trajectories of robots repel each other. With the added assumption of communication between the robots and higher computational costs, the resultant approach is near optimal and does not get the robot stuck or trapped. A variant of the algorithm with no direct communication is also presented. The method is experimented by using computer simulations and found to perform better over well-known approaches in the literature.     

Modelling cloud data using an adaptive slicing approach

In reverse engineering, the conventional surface modelling from point cloud data is time-consuming and requires expert modelling skills. One of the innovative modelling methods is to directly slice the point cloud along a direction and generate a layer-based model, which can be used directly for fabrication using rapid prototyping (RP) techniques. However, the main challenge is that the thickness of each layer must be carefully controlled so that each layer will yield the same shape error, which is within the given tolerance bound. In this paper, an adaptive slicing method for modelling point cloud data is presented. It seeks to generate a direct RP model with minimum number of layers based on a given shape error. The method employs an iterative approach to find the maximum allowable thickness for each layer. Issues including multiple loop segmentation in layers, profile curve generation, and data filtering, are discussed. The efficacy of the algorithm is demonstrated by case studies.     

Conflict free coordinated path planning for multiple robots using a dynamic path modification sequence

In this paper, a practically viable approach for conflict free, coordinated motion planning of multiple robots is proposed. The presented approach is a two phase decoupled method that can provide the desired coordination among the participating robots in offline mode. In the first phase, the collision free path with respect to stationary obstacles for each robot is obtained by employing an A* algorithm. In the second phase, the coordination among multiple robots is achieved by resolving conflicts based on a path modification approach. The paths of conflicting robots are modified based on their position in a dynamically computed path modification sequence (PMS). To assess the effectiveness of the developed methodology, the coordination among robots is also achieved by different strategies such as fixed priority sequence allotment for motion of each robot, reduction in the velocities of joints of the robot, and introduction of delay in starting of each robot. The performance is assessed in terms of the length of path traversed by each robot, time taken by the robot to realize the task and computational time. The effectiveness of the proposed approach for multi-robot motion planning is demonstrated with two case studies that considered the tasks with three and four robots. The results obtained from realistic simulation of multi-robot environment demonstrate that the proposed approach assures rapid, concurrent and conflict free coordinated path planning for multiple robots.     

Near-time optimal robot motion planning foe on-line applications

Solving current formulations of the time-optimal point-to-point motion problem for robotic manipulators is a computationally intensive task. Thus, most existing solutions are not suitable for on-line motion planning applications, such as the interception of moving targets, where time-optimality of the motion is advantageous. A novel technique is proposed in this article that separates the time-optimal point-to-point motion problem into the following two sub-problems: (1) selection of a near-time-optimal path between the two endpoints, and (2) generation of time-optimal motion along the selected path (i.e., constrained continuous path motion). Although our approach uses known path-constrained time-optimal-motion algorithms for the second sub-problem, a new method is proposed for the selection of near-time-optimal paths. Based on a study of the characteristics of global-time-optimal paths, the near-optimal path is selected as a minimum-curvature joint spline, tangent to one of the manipulator's acceleration directions at the start point, and tangent to the required manipulator velocity direction at the end point. The algorithm for determining the overall near-optimal path is described herein, along with an example. Simulation test results and computation-time studies indicate that the proposed method is suitable for on-line motion planning applications. © 1995 John Wiley & Sons, Inc.     

Formation path following control of unicycle-type mobile robots

This paper presents a control strategy for the coordination of multiple mobile robots. A combination of the virtual structure and path following approaches is used to derive the formation architecture. A formation controller is proposed for the kinematic model of two-degree-of-freedom unicycle-type mobile robots. The approach is then extended to consider the formation controller by taking into account the physical dimensions and dynamics of the robots. The controller is designed in such a way that the path derivative is left as a free input to synchronize the robot’s motion. Simulation results with three robots are included to show the performance of our control system. Finally, the theoretical results are experimentally validated on a multi-robot platform.     

Gaussian process approach for modelling of nonlinear systems

Parametric modelling principals such as neural networks, fuzzy models and multiple model techniques have been proposed for modelling of nonlinear systems. Research effort has focused on issues such as the selection of the structure, constructive learning techniques, computational issues, the curse of dimensionality, off-equilibrium behaviour, etc. To reduce these problems, the use of non-parametrical modelling approaches have been proposed. This paper introduces the Gaussian process (GP) prior approach for the modelling of nonlinear dynamic systems. The relationship between the GP model and the radial basis function neural network is explained. Issues such as selection of the dimension of the input space and the computation load are also discussed. The GP modelling technique is demonstrated on an example of the nonlinear hydraulic positioning system.     

Non-holonomic Path Planning of a Free-Floating Space Robotic System Using Genetic Algorithms

In this paper, the non-holonomic characteristic of a free-floating space robotic system is used to plan the path of the manipulator joints, by whose motion the base attitude and the manipulator joints attain the desired states. Here, we parameterize the joint trajectory using sinusoidal functions, whose arguments are high-order polynomials. Then, we define the cost function for optimization according to the constraint conditions and the accuracy of the space robot. Finally, genetic algorithms (GAs) are used to search for the solutions of the parameters. Compared with others, our approach has advantages as follows. (i) The motion of the manipulator and the disturbance on the base are practically constrained. (ii) The dynamic singularities cannot affect the algorithm since only the direct kinematic equations are utilized. (iii) The planned path is smooth and more applicable for the control of the manipulator. (iv) The convergence of the algorithm is not affected by the attitude singularity since the orientation error is represented by quaternion, which is globally singularity-free. The simulation results of the spacecraft with a 6-d.o.f. manipulator verify the performance and the validity of the proposed method.     

Fast human activity recognition based on structure and motion

We present a method for the recognition of human activities. The proposed approach is based on the construction of a set of templates for each activity as well as on the measurement of the motion in each activity. Templates are designed so that they capture the structural and motion information that is most discriminative among activities. The direct motion measurements capture the amount of translational motion in each activity. The two features are fused at the recognition stage. Recognition is achieved in two steps by calculating the similarity between the templates and motion features of the test and reference activities. The proposed methodology is experimentally assessed and is shown to yield excellent performance.     

Collision-free motion planning of dual-arm reconfigurable robots

Dual-arm reconfigurable robot is a new type of robot. It can adapt to different tasks by changing its different end-effector modules which have standard connectors. Especially, in fast and flexible assembly, it is very important to research the collision-free planning of dual-arm reconfigurable robots. It is to find a continuous, collision-free path in an environment containing obstacles. A new approach to the real-time collision-free motion planning of dual-arm reconfigurable robots is used in the paper. This method is based on configuration space (C-Space). The method of configuration space and the concepts reachable manifold and contact manifold are successfully applied to the collision-free motion planning of dual-arm robot. The complexity of dual-arm robots’ collision-free planning will reduce to a search in a dispersed C-Space. With this algorithm, a real-time optimum path is found. And when the start point and the end point of the dual-arm robot are specified, the algorithm will successfully get the collision-free path real time. A verification of this algorithm is made in the dual-arm horizontal articulated robot SCARATES, and the simulation and experiment ascertain that the algorithm is feasible and effective.     

基于区域行进策略的飞机油箱检查机器人路径规划算法

针对类似于飞机油箱环境中连续型机器人的路径规划问题,设计基于区域行进策略的路径规划算法,结合机器人本体结构约束规划到达油箱内任意给定目标点的路径。连续型机器人具有运动灵活性,但超冗余自由度导致了三维空间规划的多解性,增加了算法的复杂度。采用降低维度的方式,通过将三维空间转化为二维平面进行规划,降低了算法的时间复杂度。将飞机油箱的单舱划分为两个区域,根据目标点所处区域位置确定规划策略。最后,基于Matlab对所提算法进行仿真,实验结果验证了算法的可行性和有效性。     

Some questions of control of the robotized in-orbit assembly of large space structures

Presented was an analytical review of the foreign and domestic scientific literature published over more than two decades on the dynamics and theory of motion control of large space structures and free-flying space robots meant for assisting the astronauts or replacing them at execution of diverse maintenance operations in open space. Although many results on the design of control systems for each of the aforementioned kinds of objects are very significant taken separately, nevertheless the most important problem of using the flying robots for in-orbit assembly of the large space structures remains still unsolved. Formulated was the concept of complex approach to the problem of robot-assisted in-orbit assembly of space structures which lies in combining the algorithms of all subsystems involved in the assembly of the objects with regard for the requirements on safe interaction of the participants, high resultant precision and reliability of operation, and minimal use of the consumable fuel.