Simultaneous algorithm for trajectory planning

This paper addresses the solution of smooth trajectory planning for industrial robots in environments with obstacles using a direct method, creating the trajectory gradually as the robot moves. The presented method deals with the uncertainties associated with the lack of knowledge of kinematic properties of intermediate via‐points since they are generated as the algorithm evolves looking for the solution. Several cost functions are also proposed, which use the time that has been calculated to guide the robot motion. The method has been applied successfully to a PUMA 560 robot and four operational parameters (execution time, computational time, distance travelled and number of configurations) have been computed to study the properties and influence of each cost function on the trajectory obtained. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Rule-based trajectory segmentation for modeling hand motion trajectory

In this paper, we propose a simple but effective method of modeling hand gestures based on the angles and angular change rates of the hand trajectories. Each hand motion trajectory is composed of a unique series of straight and curved segments. In our Hidden Markov Model (HMM) implementation, these trajectories are modeled as a connected series of states analogous to the series of phonemes in speech recognition. The novelty of the work presented herein is that it provides an automated process of segmenting gesture trajectories based on a simple set of threshold values in the angular change measure. In order to represent the angular distribution of each separated state, the von Mises distribution is used. A likelihood based state segmentation was implemented in addition to the threshold based method to ensure that the gesture sets are segmented consistently. The proposed method can separate each angular state of the training data at the initialization step, thus providing a solution to mitigate the ambiguities on initializing the HMM. The effectiveness of the proposed method was demonstrated by the higher recognition rates in the experiments compared to the conventional methods.     

Optimal trajectory planning for industrial robots

An analysis of the results of an algorithm for optimal trajectory planning of robot manipulators is described in this paper. The objective function to be minimized is a weighted sum of the integral squared jerk and the execution time. Two possible primitives for building the trajectory are considered: cubic splines or fifth-order B-splines. The proposed technique allows to set constraints on the robot motion, expressed as upper bounds on the absolute values of velocity, acceleration and jerk. The described method is then applied to a 6-d.o.f. robot (a Cartesian gantry manipulator with a spherical wrist); the results obtained using the two different primitives are presented and discussed.     

Algorithms for rough terrain trajectory planning

This paper deals with motion planning on rough terrain for mobile robots. The aim is to develop efficient algorithms, suitable for various types of robots. On rough terrain, the planned trajectory must verify several validity constraints : stability of the robot, mechanical limits and collision avoidance with the ground. Our approach relies on a static and kinematic model of the robot. Efficient geometric algorithms have been developed, taking advantage of each vehicle's specificities. Motion planning relies on an incremental search in the discretized configuration space and uses efficient heuristics based on terrain characteristic to limit the size of the search space. Simulation results present trajectories planned in a few seconds. The second part takes into account uncertainties to improve trajectory robustness: uncertainties on the terrain model and the position of the robot. The adaptation of the previous algorithms allows us to find robust trajectories, without any excessive time increase.     

Energy-optimal trajectory planning for car-like robots

When a battery-powered robot needs to operate for a long period of time, optimizing its energy consumption becomes critical. Driving motors are a major source of power consumption for mobile robots. In this paper, we study the problem of finding optimal paths and velocity profiles for car-like robots so as to minimize the energy consumed during motion. We start with an established model for energy consumption of DC motors. We first study the problem of finding the energy optimal velocity profiles, given a path for the robot. We present closed form solutions for the unconstrained case and for the case where there is a bound on maximum velocity. We then study a general problem of finding an energy optimal path along with a velocity profile, given a starting and goal position and orientation for the robot. Along the path, the instantaneous velocity of the robot may be bounded as a function of its turning radius, which in turn affects the energy consumption. Unlike minimum length paths, minimum energy paths may contain circular segments of varying radii. We show how to efficiently construct a graph which generalizes Dubins’ paths by including segments with arbitrary radii. Our algorithm uses the closed-form solution for the optimal velocity profiles as a subroutine to find the minimum energy trajectories, up to a fine discretization. We investigate the structure of energy-optimal paths and highlight instances where these paths deviate from the minimum length Dubins’ curves. In addition, we present a calibration method to find energy model parameters. Finally, we present results from experiments conducted on a custom-built robot for following optimal velocity profiles.     

SMArDT modeling for automotive software testing

Efficient testing is a crucial prerequisite to engineer reliable automotive software successfully. However, manually deriving test cases from ambiguous textual requirements is costly and error-prone. Model-based software engineering captures requirements in structured, comprehensible, and formal models, which enables early consistency checking and verification. Moreover, these models serve as an indispensable basis for automated test case derivation. To facilitate automated test case derivation for automotive software engineering, we conducted a survey with testing experts of the BMW Group and conceived a method to extend the BMW Group's specification method for requirements, design, and test methodology by model-based test case derivation. Our method is realized for a variant of systems modeling language activity diagrams tailored toward testing automotive software and a model transformation to derive executable test cases. Hereby, we can address many of the surveyed practitioners' challenges and ultimately facilitate quality assurance for automotive software.     

基于信赖域算法的机械臂时间最优轨迹规划

为了提高机械臂的工作效率,提出了一种新的时间最优轨迹规划方法.通过逆运动学运算得到与任务空间轨迹对应的关节空间位置序列,采用7次B样条曲线构造关节空间插值轨迹,将运动学约束转换为对B样条轨迹曲线控制顶点的约束,并适当放大约束条件,然后采用信赖域方法求解时间优化问题,从而规划出速度、加速度和脉动均连续且满足运动学约束的时间最优轨迹.仿真结果验证了所提出时间最优轨迹规划方法的有效性.     

基于AGA的时间最优机械臂轨迹规划算法*

根据机械臂运动学约束,提出了关节空间基于自适应遗传算法(AGA)的3-5-3多项式插值轨迹规划算法。利用运动学约束,以最优时间为目标,针对关节型机器人在静态环境下点到点的轨迹规划问题,利用AGA算法解算多项式插值的时间。通过与基于GA的3-5-3多项式机械臂轨迹规划进化曲线和运动位置、速度、加速度曲线对比,证明该方法在算法收敛、运行平稳度上都有突出优点。     

B-splines joint trajectory planning

This paper describes how B-splines can be used to construct joint trajectories for robot manipulators. The motion is specified by a sequence of Cartesian knots, i.e., positions and orientations of the end effector of a robot manipulator. For a six joint robot manipulator, these Cartesian knots are transformed into six sets of joint variables, with each set corresponding to a joint. Splines, represented as linear combinations of B-splines, are used to fit the sequence of joint variables for each of the six joints. A computationally very simple recurrence formula is used to generate the B-splines. This approach is used for the first time to establish the mathematical model of trajectory generation for robot manipulators, and offers flexibility, computational efficiency, and a compact representation.     

Evolutionary trajectory planning for an industrial robot

This paper presents a novel general method for computing optimal motions of an industrial robot manipulator (AdeptOne XL robot) in the presence of fixed and oscillating obstacles. The optimization model considers the nonlinear manipulator dynamics, actuator constraints, joint limits, and obstacle avoidance. The problem has 6 objective functions, 88 variables, and 21 constraints. Two evolutionary algorithms, namely, elitist non-dominated sorting genetic algorithm (NSGA-II) and multi-objective differential evolution (MODE), have been used for the optimization. Two methods (normalized weighting objective functions and average fitness factor) are used to select the best solution tradeoffs. Two multi-objective performance measures, namely solution spread measure and ratio of non-dominated individuals, are used to evaluate the Pareto optimal fronts. Two multi-objective performance measures, namely, optimizer overhead and algorithm effort, are used to find the computational effort of the optimization algorithm. The trajectories are defined by B-spline functions. The results obtained from NSGA-II and MODE are compared and analyzed.     

一类无冲突轨迹规划方案

在新一代空中交通管理自动化系统实施方案中,航迹规划模块在基于航迹的航空器运行过程中扮演着重要角色.为了在大流量、高密度和小间隔条件下获取多航空器无冲突轨迹,针对不同的航路空间分布结构,基于航路冲突点保护区竞争机制,构建了空域多航空器极大代数耦合模型和多航空器冲突预调配模型,根据管制间隔约束建立了模型输入、状态和输出之间的约束关系.采用调整航空器过冲突点时刻和初始放行时刻两种策略,提出了一种多航空器轨迹规划优化模型.算例分析表明,所提出的多航空器轨迹规划模型可行有效.     

Joint space trajectory planning for flexible manipulators

A trajectory planning approach for controlling flexible manipulators is proposed. It is demonstrated that choosing actual joint angles as the generalized rigid coordinates is the key to applying the proposed approach. From the observation of the special structure of the input matrix, the concepts of motion-induced vibration and inverse dynamics under a specified motion history of the joints are formed naturally. Based on the above concepts, trajectory planning in joint space is proposed by using the optimization technique to determine the motion of joints along a specified path in joint space or work space and for general point-to-point motion. The motion for each joint is assumed to be in a class consisting of a fifth-order polynomial and a finite terms of Fourier series. This parameterization of motion allows the optimal trajectory planning to be formulated as a standard nonlinear programming problem, which avoids the necessity of solving a two-point-boundary-value problem and using dynamic programming. Setting the accelerations to zero at the initial and the final times is used to obtain smoother motion to reduce the spillover energy into unmodeled high-frequency dynamics. A penalty term on vibration energy contained in the performance index is used to minimize the vibration of the system modeled by lower frequency only. The final simulation results show the effectiveness of the proposed approach and the advantage for proper trajectory planning. © 2995 John Wiley & Sons, Inc.     

An adaptive parametric interpolator for trajectory planning

A real-time interpolation algorithm for trajectory planning is studied in this paper. The NURBS interpolation algorithm is proposed to confine contour errors and feedrate fluctuations. The feedrate is adjusted adaptively according to the specified acceleration/deceleration values and jerk value. A direct digital convolution method is also introduced into velocity planning for NURBS interpolator, and it is more efficient than the traditional method of polynomial functions. The feedrate at the sharp corner is smoothed by imposing limitations on the acceleration and jerk values generated in the machining process. Since the computation of the total length of NURBS curve is required for the digital convolution method, a numerical adaptive quadrature algorithm is used to approximate the integrand. Simulation results demonstrate the effectiveness of the proposed interpolator for machining curved paths.     

面向多目标侦察任务的无人机航线规划

针对无人机执行多目标侦察任务的航线规划问题,提出一种改进粒子群算法结合高斯伪谱法的分层航线规划方法.设计改进粒子群算法进行航线预规划,针对传统粒子群优化算法收敛速度慢、易陷入局部最优的问题,通过引入混沌映射初始化和自适应参数调整策略,加快算法收敛速度,提升解的最优性.在此基础上,结合最短路求解策略,完成对侦察任务的时序...     

Neural-networks-based nonlinear dynamic modeling for automotive engines

This paper presents a procedure for using neural networks to identify the nonlinear dynamic model of the intake manifold and the throttle body processes in an automotive engine. A dynamic neural network called external recurrent neural network, is used for dynamic mapping and model construction. Dynamic Levenberg–Marquardt algorithm is then applied to the weight-estimation problem. Modeling results indicate that the neural-network-based models have a rather simple structure. Early results also confirm that the neural-network-based modeling of the manifold dynamics can result in a model that is comparable if not better than the first-principle-based models. In addition, it was verified that the neural model has good generalization capabilities.     

基于APSODE-MS算法的无人机航迹规划

无人机航迹规划是指在环境威胁与自身约束条件下,规划一条安全可行的航迹,是实现无人机自主化飞行的关键技术之一.为实现无人机在不同城市环境下能够快速规划一条安全可靠的航迹,提出一种基于自适应粒子群差分进化-最小捕捉(APSODE-MS)算法的无人机航迹规划方法.首先,建立城市环境航迹规划数学模型,以航程距离、威胁约束、违背约束代价3者的加权和作为目标函数;其次,在PSO算法中引入自适应非线性惯性权重,根据粒子偏离全局最优解的程度分配不同的搜索模式,结合动态差分进化(DE)算法加快粒子的收敛速度,引入改进的正态扰动提高跳出停滞与早熟现象的能力;最后,筛选关键航迹点,并采用最小捕捉轨迹(MS)算法对航迹进行光滑处理.仿真结果表明,所提出的APSODE-MS航迹规划方法能够在不同城市仿真环境下较好地完成规划任务,并能获得更优的航路,从而验证算法的有效性和鲁棒性.     

羽毛球机器人机械臂运动轨迹多目标规划

为了实现羽毛球机器人机械臂高速连续平滑地击打羽毛球动作,提出了一种新的多目标机械臂运动轨迹优化模型。首先,该轨迹优化模型根据D-H运动学模型,通过坐标变换建立机械臂的位姿表达式。然后,采用牛顿下山法求出给定路径关键点的运动学逆解集,并基于最短路径算法从逆解集中求出最优解。最后,根据所求出最优解,采用三次样条插值建立电机转角函数,以实现机械臂的连续平滑运动。实验结果表明：新的轨迹优化模型能够有效地降低电机能耗和提高转动效率,从而保证了机械臂响应速度。     

机器人的CP-nets优化类人轨迹规划

机器人移动轨迹按照人的手臂来模拟是提高机器人安全性和人机交互能力的有效方法,特别是针对机器人抓取路径不唯一的场合,类人行为对于人机系统表现更加自然。此前,通常利用Kinect等设备,基于人工神经网络和K近邻算法等智能算法对类人轨迹进行规划,但无法获得未采样过的最优轨迹。本文基于CP-nets采用偏好模型研究类人运动轨迹,然后将该模型应用于机器人控制,在没有采样的情况下,也可得到最优的类人轨迹。实验结果表明,基于CP-nets 的类人规划轨迹具有较高的效率和舒适性,符合人的运动特征。     

User satisfaction modeling framework for automotive audio interfaces

Currently the research on product satisfaction is evolving to integrate pleasure and delight alongside other, more traditional needs. Pleasure and delight are emotional and hedonic benefits experienced by the user when interacting with the product. Thus, user satisfaction models have to deal with high complexity of product properties that collectively contribute to satisfaction. The formulation of these models has to include not only a proper taxonomy, but also the organization of such properties in categories and their relation to well defined satisfaction dimensions. Successful models would help to find out the most effective technical and design specifications (engineering parameters) that give shape to specific attributes of design, sometimes called “brand feelings”, defined in accordance with the business strategy. The objective of this paper is to present a user satisfaction modeling framework that deals with the complexity of an in-car user interface, namely the audio one. The proposed framework defines three distinct types of product properties: engineering parameters (P), perceived product attributes (A) and satisfaction dimensions (D) and presents a methodology to link the perceived product attributes (A) to satisfaction dimension (D).