基于伪谱法的编队卫星队形重构防碰撞轨迹优化

提出了基于伪谱法的编队卫星队形重构最优轨迹规划方法.首先,应用Legendre伪谱法将队形重构问题离散化为非线性规划问题;然后,通过庞特里亚金极小值原理计算出不考虑碰撞规避问题时各星最优轨迹的解析形式,并由此计算出各星间的碰撞点;最后,在碰撞点附近设置符合高斯分布的测试点,进一步避免各星在配置点间发生碰撞.仿真结果表明,应用所提出方法得到的队形重构的最优轨迹能够较好地满足各种约束条件,计算精度高、速度快,使得编队卫星自主重构成为可能.     

Path planning for collision avoidance using a glid-like space

Many remote-control robots are being developed. And they are hoped to work in extreme environmental conditions such as lifesaving or rescue. These robots required complicate movement and precise works. Almost remote controller are often discussed for the position control on the end effector under camera images. However, it is difficult to control a robot arm using limited information in the monitor, as it is difficult for personnel to perform sensitive work while controlling a robot with the limited view information. This results in high stress for the driver and can cause operational mistakes. Therefore, it is important to use robot easily under a limited view. In this report, we propose a simplification method for a beginner user. We present a computed support system to control the robot arm easily with increased sensitivity, combined with grid-like space and a joystick.     

Obstacle avoidance in a dynamic environment: a collision coneapproach

A novel collision cone approach is proposed as an aid to collision detection and avoidance between irregularly shaped moving objects with unknown trajectories. It is shown that the collision cone can be effectively used to determine whether collision between a robot and an obstacle (both moving in a dynamic environment) is imminent. No restrictions are placed on the shapes of either the robot or the obstacle, i.e., they can both be of any arbitrary shape. The collision cone concept is developed in a phased manner starting from existing analytical results that enable prediction of collision between two moving point objects. These results are extended to predict collision between a point and a circular object, between a point and an irregularly shaped object, between two circular objects, and finally between two irregularly shaped objects. Using the collision cone approach, several strategies that the robot can follow in order to avoid collision, are presented. A discussion on how the shapes of the robot and obstacles can be approximated in order to reduce computational burden is also presented. A number of examples are given to illustrate both collision prediction and avoidance strategies of the robot     

双臂空间机器人的避自碰轨迹规划研究*

本文针对自由漂浮的双臂空间机器人系统研究了一种基于危险域的避自碰轨迹规划方案。首先,引入危险域的概念,用来评估两个机械臂之间发生碰撞的危险程度。其次,在路径规划的基础之上,利用危险域的反馈信息,设计了一种安全避自碰的轨迹规划方案,用以保证两个机械臂可以运动在安全位型,从而避免发生自碰。最后,针对一个双臂冗余空间机器人系统进行运动仿真,仿真结果验证了本文方法的有效性。     

Cooperative path planning with priority target assignment and collision avoidance guidance for rescue unmanned surface vehicles in a complex ocean environment

In this paper, a novel cooperative path planning scheme of unmanned surface vehicles (USVs) for rescuing targets in a complex ocean environment is proposed. The primary objective of the rescue USVs is to bring all targets back safely on the premise of first rescuing priority targets, while optimizing the path length, the navigation time and the angular energy. The main contributions of this paper are as follows: (1) The proposed K-means-division (KMD) algorithm is able to identify a complex ocean environment with collision-free zone and static-obstacles zone; (2) The proposed path planning method with fast-marching-method-based ellipse guidance range (E-FMM) is able to optimize the angular energy while ensuring safety; (3) The proposed cooperative management system (including priority-target-assignment (PTA) with reward-mechanism genetic-optimization (RM-GO) and collision-avoidance (CA) guidance law with Tangent-based surge-varying wave-disturbances-observer (Tangent-SV-WDO)) can accomplish the mission of the rescue USVs. Comparative studies with the state-of-the-art methods demonstrate that the proposed cooperative path planning scheme is superior in terms of priority-target-assignment (PTA) and collision-avoidance (CA) of the actual rescue work.     

多障碍环境中移动机器人的光滑轨迹规划

根据轮式移动机器人参数化轨迹生成模型,结合多障碍物结构化环境中障碍物的建模,把其和参数化轨迹规划模型融合,得到了具有一般性的多障碍物环境中轮式移动机器人光滑轨迹规划模型;并利用最优化控制原理,建立了任意性能指标下,多障碍物环境中最优参数化轨迹生成模型。结合数值求解方法,推导了多障碍物环境中参数化轨迹规划非线性求解模型的求解方法。最后通过仿真验证了参数化轨迹规划求解模型的正确性。     

Rendezvous-guidance trajectory planning for robotic dynamic obstacle avoidance and interception.

This correspondence presents a novel online trajectory-planning method for the autonomous robotic interception of moving targets in the presence of dynamic obstacles, i.e., position and velocity matching (also referred to as rendezvous). The proposed time-optimal interception method is a hybrid algorithm that augments a novel rendezvous-guidance (RG) technique with the velocity-obstacle approach, for obstacle avoidance, first reported by Fiorini and Shiller. The obstacle-avoidance algorithm itself could not be used in its original form and had to be modified to ensure that the online planned path deviates minimally from the one generated by the RG algorithm. Extensive simulation and experimental analyses, some of which are reported in this correspondence, have clearly demonstrated the tangible time efficiency of the proposed interception method.     

机器人在已知三维自然环境中的路径规划算法

研究了移动机器人在三维环境的路径规划问题,针对该问题中存在环境适应性和全局性差的不足,对人工势场法进行改进,提出了一种新的路径规划的算法.该算法首先对已知的三维自然环境进行栅格化,建立栅格运行费用的评估模型,计算每个栅格的运行费用;然后依据栅格的运行费用建立斥力场,以目标点为中心的建立引力场,同时提出解决局部最小值的问题的方法;最后将两者合力的方向作为移动机器人在该点的路径走向,规划出一条从起始点到目标点的运行费用较低的路径.仿真实验结果表明,该算法能有效降低运行费用,适应性和全局性好,适合应用于移动机器人在三维自然环境中的路径规划.     

A local obstacle avoidance method for mobile robots in partially known environment

Local obstacle avoidance is a principle capability for mobile robots in unknown or partially known environment. A series of velocity space methods including the curvature velocity method (CVM), the lane curvature method (LCM) and the beam curvature method (BCM) formulate the local obstacle avoidance problem as one of constrained optimization in the velocity space by taking the physical constraints of the environment and the dynamics of the vehicle into account. We present a new local obstacle avoidance approach that combines the prediction model of collision with the improved BCM. Not only does this method inherit the quickness of BCM and the safety of LCM, but also the proposed prediction based BCM (PBCM) can be used to avoid moving obstacles in dynamic environments.     

Improving collision avoidance for mobile robots in partially known environments: the beam curvature method

This paper presents a new approach to obstacle avoidance for mobile robots in cluttered and unknown or partially unknown environments. The method combines a new directional method, called beam method (BM), to improve the performance of a local obstacle avoidance approach called curvature velocity method (CVM). BM calculates the best one-step heading which is used by CVM to obtain the optimal linear and angular velocities. The resulting combined technique is called beam curvature method (BCM).

Different experiments in populated and dynamic environments have proved to be very successful. The method is able to guide the robot safely and efficiently during long time periods. We present some of these results compared with other methods.     

VCS-based motion planning for distributed mobile robots: collision avoidance and formation

This paper addresses decentralized motion planning among a homogeneous set of feedback-controlled mobile robots. It introduces the velocity obstacle, which describes the collision between robot and obstacle, and the hybrid interactive velocity obstacles are designed for collision checking between interacting robots. The (sub)goal selection algorithm is also studied for formation control, then the preferred velocity is designed for robot tracking its desired (sub)goal. Furthermore, the rules for the size regulation of obstacle are presented to avoid conservative motion planning and enhance the safety. Then, we establish a novel Velocity Change Space (VCS), map the velocity obstacles, the desired (sub)goal and the reachable velocity change window before collision in this space, and directly get the new velocity by a multi-objective optimization method. We apply VCS-based motion planning methods to distributed robots, and simulation is used to illustrate the good performances with respect to the un-conservative, foresighted and multi-objective optimal motion planning, especially the successful application in the formation control of the multi-robot system.     

Prioritized planning algorithm for multi-robot collision avoidance based on artificial untraversable vertex

Applied Intelligence - This paper presents a method to avoid collisions and deadlocks between mobile robots working collaboratively in a shared physical environment. Based on the shared knowledge...     

基于时间窗的AGV动态避碰路径规划方法

为了解决多AGV在动态不稳环境下的无碰撞路径规划和系统效率提升的问题,提出了基于时间窗的AGV无碰撞路径规划方法。首先建立了多AGV的避碰模型,并结合时间窗模型,将多AGV的无碰撞路径规划分为预先规划和实时规划两阶段,预先规划阶段进行多AGV无冲突时间窗的计算和最大化系统中AGV的流通量,实时规划阶段通过改变AGV在避碰模型上的占用优先级和局部重规划的方法进行动态避碰。最后以某智能仓储为应用案例进行仿真实验,证明了该算法能有效避免多AGV的碰撞,提高AGV的流通量,同时在动态环境下具有较好的鲁棒性和柔性。     

Vision-based navigation frame mapping and planning for collision avoidance for miniature air vehicles

This paper presents a vision-based navigation frame mapping and path planning technique for collision avoidance for Miniature Air Vehicles. A depth map that represents the range and bearing to obstacles is obtained by computer vision. Based on the depth map, an extended Kalman Filter is used to estimate the range and bearing. Using this information, a map, constructed in polar coordinates, is created in the navigation frame of the MAV. The Rapidly-exploring Random Tree algorithm is employed to find a collision-free path in the navigation frame. The proposed algorithm was successfully implemented in both simulation and flight tests.     

多搬运任务下考虑碰撞避免的AGV路径规划

为提升自动导引小车在“货到人”仓库中的运行效率,针对AGV-托盘任务分配、单AGV路径规划及多AGV碰撞避免三个子问题的研究,以最小化AGV行驶距离为目标构建数学模型。首先,根据AGV与托盘的双边匹配问题特点设计改进的匈牙利算法求解匹配结果。其次,提出一种二维编码机制的改进遗传算法（improved genetic algorithm,IGA）,采用一种局部搜索算子代替原变异操作,在提高算法搜索性能的基础上使其成功应用于单AGV路径规划问题。然后,利用时空数据设计一种三维网格冲突检测方法,并根据商品SKU数量设定AGV的优先级以降低多AGV执行任务时的碰撞概率。最后,在32 m×22 m的仓库中针对不考虑碰撞与考虑碰撞两种情形进行AGV路径优化分析,给出合理的行驶距离和碰撞次数。IGA与标准遗传算法的对比结果显示,IGA能够在合理的时间内获得更高质量的解,行驶距离减少约1.74%,算法求解时间缩短约37.07%。此外,针对AGV数量灵敏度分析,在不同目标托盘规模下测试不同数量的AGV对行驶距离和碰撞次数的影响,发现14~16台AGV数量是最佳配置,验证了模型的可行性和算法的有效性。     

Intelligent collision avoidance planning of a robot manipulator whose workspace includes moving objects

The collision avoidance problem of a robot manipulator whose workspace includes moving objects is considered in this paper. It is shown that the proposed computer simulation system can be used in a dialogue mode with a designer to check whether or not collision with obstacles is avoided and to determine the appropriate movement.     

Optimal and suboptimal motion planning for collision avoidance of mobile robots in non-stationary environments

An optimal control formulation of the problem of collision avoidance of mobile robots moving in terrains containingmoving obstacles is presented. A dynamic model of the mobile robot and the dynamic constraints are derived. Collision avoidance is guaranteed if the minimum distance between the robot and the objects is nonzero. A nominal trajectory is assumed to be known from off-line planning. The main idea is to change the velocity along the nominal trajectory so that collisions are avoided. Furthermore, time consistency with the nominal plan is desirable. Two solutions are obtained: (1) A numerical solution of the optimization problem and a perturbation type of control to update the optimal plan and (2) A computationally efficient method giving near optimal solutions. Simulation results verify the value of the proposed strategies and allow for comparisons.     

Fusion of laser and visual data for robot motion planning and collision avoidance

In this paper, a method for inferring scene structure information based on both laser and visual data is proposed. Common laser scanners employed in contemporary robotic systems provide accurate range measurements, but only in 2D slices of the environment. On the other hand, vision is capable of providing dense 3D information of the environment. The proposed fusion scheme combines the accuracy of laser sensors with the broad visual fields of cameras toward extracting accurate scene structure information. Data fusion is achieved by validating 3D structure assumptions formed according to 2D range scans of the environment, through the exploitation of visual information. The proposed methodology is applied to robot motion planning and collision avoidance tasks by using a suitably modified version of the vector field histogram algorithm. Experimental results confirm the effectiveness of the proposed methodology.Received: 10 May 2002, Accepted: 18 December 2002, Published online: 7 October 2003     

Positioning and obstacle avoidance of automatic guided vehicle in partially known environment

This paper presents positioning and obstacle avoidance of Automatic Guidance Vehicle (AGV) in partially known environment. To do this task, the followings are done. Firstly, the system configuration of AGV is described. Secondly, mathematical kinematic modeling of the AGV is presented to understand its characteristics and behavior. Thirdly, the Simultaneous Localization and Mapping (SLAM) algorithm based on the laser measurement system and encoders is proposed. The encoders are used for detecting the motion state of the AGV. In a slippery environment and a high speed AGV condition, encoder positioning method generates big error. Therefore, Extended Kalman Filter (EKF) is used to get the best position estimation of AGV by combining the encoder positioning result and landmark positions obtained from the laser scanner. Fourthly, to achieve the desired coordinate, D* Lite algorithm is used to generate a path from the start point to the goal point for AGV and to avoid unknown obstacles using information obtained from laser scanner. A backstepping controller based on Lyapunov stability is proposed for tracking the desired path generated by D* Lite algorithm. Finally, the effectiveness of the proposed algorithms and controller are verified by using experiment. The experimental results show that the AGV successfully reaches the goal point with an acceptable small error.     

多障碍物环境下挖掘机的连续避障轨迹规划

针对多障碍物环境下,挖掘机在挖掘过程中,铲斗碰到障碍物无法进行适应性调整的问题,利用三次多项式和积分法规划挖掘轨迹,采用盲人摸路算法对挖掘过程中挖掘机与障碍物发生碰撞后进行及时有效的调整,运用原像规划算法判断避障方向。为了方便进行避障算法验证,利用Matlab图形用户界面（GUI）设计了一个能够实现参数设置、结果展示等功能的可视化界面。仿真实验表明,该避障算法能够在复杂环境中,多次平滑绕开障碍物来完成连续避障任务。