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.     

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.     

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.     

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.     

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.     

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).     

基于改进RRT-connect的四旋翼无人机避障轨迹规划算法

针对四旋翼无人机在低空复杂环境自主巡航所需的航迹规划问题,提出了一种基于快速搜索随机树(RRT-connect)的改进型算法。根据四旋翼无人机的微分平坦特性,合理设计了规划空间;引入转角约束和路径修剪方法,在保证规划实时性的基础上使所规划路径的平均长度缩短了19%;通过B样条函数对路径进行平滑处理,使生成的轨迹具有二阶几何连续性,同时能避免与障碍物区域发生碰撞。经多次重复对比试验,证实了提出算法的有效性、优越性和稳定性。     

基于混合遗传算法的工业机器人最优轨迹规划

为兼顾工业机器人工作效率与轨迹的平稳性,提出一种基于混合遗传算法的二次轨迹规划方案.通过最优时间轨迹规划得到最小执行时间,在最小执行时间内进行最优冲击轨迹规划,进而规划出一条既高效又平滑的运动轨迹.采用五次均匀B样条在关节空间进行快速插值,不仅保证了各关节速度和加速度连续性还保证了各关节冲击的连续性.连续平滑的冲击可以减少机械振动,延长机器人的工作寿命.选用PUMA560为对象进行仿真与实验,结果表明,该方案可以获得比较理想的机器人运动轨迹,所提出的混合遗传算法能有效提高全局寻优的性能和算法运行的稳定性.     

Robust trajectory planning for robotic manipulators under payload uncertainties

A number of trajectory planning algorithms are available for determining the joint torques, positions, and velocities required to move a manipulator along a given geometric path in minimum time. These schemes require knowledge of the robot's dynamics, which in turn depend upon the characteristics of the payload which the robot is carrying. In practice, the dynamic properties of the payload will not be known exactly, so that the dynamics of the robot, and hence the required joint torques, must be calculated for a nominal set of payload characteristics. But since these trajectory planners generate nominal joint torques which are at the limits of the robot's capabilities, moving the robot along the desired geometric path at speeds calculated for the nominal payload may require torques which exceed the robot's capabilities. In this paper, bounds on joint torque uncertainties are derived in terms of payload uncertainties. Using these bounds, a new trajectory planner is developed to incorporate payload uncertainties such that all the trajectories generated can be realized with given joint torques. Finally, the trajectory planner is applied to the first three joints of the Bendix PACS arm, a cylindrical robot to demonstrate its use and power.     

Model-based trajectory planning for flexible-link mechanisms with bounded jerk

This paper deals with the model-based development of optimal jerk-limited point-to-point trajectories for flexible-link robotic manipulators. In the proposed approach, an open-loop optimal control strategy is applied to an accurate dynamic model of flexible multi-body planar mechanisms. The model, which has already been fully validated through experimental tests, is based on finite element discretization and accounts for the main geometric and inertial non-linearities of the linkage. Exploiting an indirect variational solution method, the necessary optimality conditions deriving from Pontryagin's minimum principle are imposed, and lead to a differential Two-Point Boundary Value Problem (TPBVP); numerical solution of the latter is accomplished by means of collocation techniques. The resulting motion and control profiles can be used as feedforward reference signals for a position and vibration control. Considering a lightweight RR robot, simulation results are provided for rest-to-rest, jerk-limited trajectories with minimum actuator jerks and vibrations. However, the strategy under investigation has general validity and can be applied to other types of mechanisms, as well as with different objective functions and boundary conditions. Numerical evidence clearly indicates that the use of a composite cost functional and the imposition of jerk constraints can greatly reduce vibration phenomena during high-speed motion of flexible-link manipulators.     

Continuous trajectory planning of mobile sensors for informative forecasting

This paper addresses the planning of continuous paths for mobile sensors to reduce the uncertainty in some quantities of interest in the future. The mutual information between the measurement along the continuous path and the future verification variables defines the information reward. Two expressions for computing this mutual information are presented: the filter form extended from the state of the art and the smoother form inspired by the conditional independence structure. The key properties of the approach using the filter and smoother strategies are presented and compared. The smoother form is shown to be preferable because it provides better computational efficiency, facilitates easy integration with existing path synthesis tools, and, most importantly, enables correct quantification of the rate of information accumulation. A spatial interpolation technique is used to relate the motion of the sensor to the evolution of the measurement matrix, which leads to the formulation of the optimal path planning problem. A gradient-ascent steering law based on the concept of information potential field is also presented as a computationally efficient suboptimal strategy. A simplified weather forecasting example is used to compare several planning methodologies and to illustrate the potential performance benefits of using the proposed planning approach.     

Time-optimal trajectory planning in cable-based manipulators

In this paper, the trajectory planning of high-speed cable-based parallel manipulators is studied for a given geometrical path. The time-optimal trajectory-planning technique is adapted for these manipulators in which cable forces must be maintained tensile. This condition is represented as a constraint on the acceleration of the end-effector along the path. The results of this technique are evaluated experimentally on DeltaBot, a cable-based manipulator developed at the University of Waterloo. The performance of the time-optimal technique is examined both for the moving time of the manipulator and the computational time of the trajectory generation.     

Intelligent computing budget allocation for on-road trajectory planning based on candidate curves

In this paper, on-road trajectory planning is solved by introducing intelligent computing budget allocation (ICBA) into a candidate-curve-based planning algorithm, namely, ordinal-optimization-based differential evolution (OODE). The proposed algorithm is named IOODE with ‘I’ representing ICBA. OODE plans the trajectory in two parts: trajectory curve and acceleration profile. The best trajectory curve is picked from a set of candidate curves, where each curve is evaluated by solving a subproblem with the differential evolution (DE) algorithm. The more iterations DE performs, the more accurate the evaluation will become. Thus, we intelligently allocate the iterations to individual curves so as to reduce the total number of iterations performed. Meanwhile, the selected best curve is ensured to be one of the truly top curves with a high enough probability. Simulation results show that IOODE is 20% faster than OODE while maintaining the same performance in terms of solution quality. The computing budget allocation framework presented in this paper can also be used to enhance the efficiency of other candidate-curve-based planning methods.     

Constraint-based sensor planning for scene modeling

We describe an automated scene modeling system that consists of two components operating in an interleaved fashion: an incremental modeler that builds solid models from range imagery; and a sensor planner that analyzes the resulting model and computes the next sensor position. This planning component is target-driven and computes sensor positions using model information about the imaged surfaces and the unexplored space in a scene. The method is shape-independent and uses a continuous-space representation that preserves the accuracy of sensed data. It is able to completely acquire a scene by repeatedly planning sensor positions, utilizing a partial model to determine volumes of visibility for contiguous areas of unexplored scene. These visibility volumes are combined with sensor placement constraints to compute sets of occlusion-free sensor positions that are guaranteed to improve the quality of the model. We show results for the acquisition of a scene that includes multiple, distinct objects with high occlusion     

基于关节轨迹规划对行人步态的仿真

为提高智能车辆的行人检测成功率,同时保证人身安全,提出一套完整的仿行人步态装置研发流程,通过建模仿真的方法促进该装置的研发并降低成本。仿真模型按照人体真实数据进行设计,步态的变化主要体现在四肢上;利用D-H参数法和正逆运动学知识,结合MATLAB建模和关节轨迹规划的方法,实现运动仿真;成功模拟出行人步态,得出仿真模型的末端轨迹、关节转角等步态指标在一个周期内的变化。将仿真结果与标准人类行走周期图谱进行了对比验证,保证了仿真模型的结构设计以及运动学模型的合理性,为后续的实际开发提供一定理论依据。     

LMIs for constrained polynomial interpolation with application in trajectory planning

We consider an open-loop trajectory planning problem for linear systems with bound constraints originating from saturations or physical limitations. Using an algebraic approach and results on positive polynomials, we show that this control problem can be cast into a constrained polynomial interpolation problem admitting a convex linear matrix inequality (LMI) formulation.     

面向无人机电力巡检航迹规划的语义服务方法

针对复杂环境下无人机电力巡检航迹规划问题,从信息处理角度提出一种语义服务方法.构建一个具有环境态势感知、航迹构造和语义策略图模型的语义服务框架;利用巡检关联比重对实体对象进行空间划分,通过OWL形式化表示和J ena推理刻画巡检航线特征位置的因果关系,提出语义空间距离计算和基于强化学习的路径选择机制.研发语义服务模拟演...     

基于卷积曲面的几何造型方法

卷积曲面是一种很有潜力的隐式曲面造型方法。由于卷积的可叠加性质,使得其生成的曲面很光滑,不会产生凸包和裂缝。卷积曲面造型是基于骨架的,其骨架可以是曲线或曲面,也可以以物体轮廓线为骨架原型来获取所需要的物体造型。在卷积造型的过程中,通过对骨架加权可以精细地控制结果曲面的形状。在介绍了卷积曲面造型的各类方法后,分析了其特点和发展方向。