Collision avoidance strategy optimization based on danger immune algorithm

Marine collision accidents cause a great loss of lives and property. As a possible solution, the danger immune algorithm is used to achieve ship collision avoidance strategy optimization, which is a multi-objective problem concerning safety and economy. Collision avoidance operations are encoded as the individuals of optimization algorithm. In the system, ship domain and ship arena, among others, are used for collision risk evaluation to assess the fitness of individuals. Through the optimization, the navigator will obtain the optimal collision avoidance strategy to achieve safe and efficient collision avoidance. The simulations indicate that the optimization algorithm is valid.     

Collision avoidance in cloth animation

For cloth modeling and animation, we use a physically based model to simulate the dynamic formation of folds, pleats, and wrinkles and the final static appearance of cloth draped over a rigid object. To simulate the behavior of the cloth and its final static appearance on the model, we propose a new collision and self-collision avoidance method to prevent penetration between the cloth and rigid objects and between parts of the cloth. At each time step, we enforce constraints over those grid points about to penetrate other objects. Our method is easier and more robust than conventional methods at representing interaction between the cloth and various objects.     

Collision avoidance between UAV clusters using swarm intelligence techniques

In this article, several basic swarming laws for Unmanned Aerial Vehicles (UAVs) are developed for both two-dimensional (2D) plane and three-dimensional (3D) space. Effects of these basic laws on the group behaviour of swarms of UAVs are studied. It is shown that when cohesion rule is applied an equilibrium condition is reached in which all the UAVs settle at the same altitude on a circle of constant radius. It is also proved analytically that this equilibrium condition is stable for all values of velocity and acceleration. A decentralised autonomous decision-making approach that achieves collision avoidance without any central authority is also proposed in this article. Algorithms are developed with the help of these swarming laws for two types of collision avoidance, Group-wise and Individual, in 2D plane and 3D space. Effect of various parameters are studied on both types of collision avoidance schemes through extensive simulations.     

Observability-based local path planning and obstacle avoidance using bearing-only measurements

In this paper we present an observability-based local path planning and obstacle avoidance technique that utilizes an extended Kalman Filter (EKF) to estimate the time-to-collision (TTC) and bearing to obstacles using bearing-only measurements. To ensure that the error covariance matrix computed by an EKF is bounded, the system should be observable. We perform a nonlinear observability analysis to obtain the necessary conditions for complete observability of the system. These conditions are used to explicitly design a path planning algorithm that enhances observability while simultaneously avoiding collisions with obstacles. We analyze the behavior of the path planning algorithm and specially define the environments where the path planning algorithm will guarantee collision-free paths that lead to a goal configuration. Numerical results show the effectiveness of the planning algorithm in solving single and multiple obstacle avoidance problems while improving the estimation accuracy.     

An algorithm for multi-robot collision-free navigation based on shortest distance

This paper presents a new approach for multi-robot navigation in dynamic environments, called the shortest distance algorithm. This approach uses both the current position and orientation of other robots to compute the collision free trajectory. The algorithm suggested in this paper is based on the concept of reciprocal orientation that guarantees smooth trajectories and collision free paths. All the robots move either in a straight line or in a circular arc using the Bresenham algorithms. The current approach is tested on three simulation scenarios.     

The SDRE control of mobile base cooperative manipulators: Collision free path planning and moving obstacle avoidance

This work proposes application of a state-dependent Riccati equation (SDRE) controller for wheeled mobile cooperative manipulators. Implementation of the SDRE on a wheeled mobile manipulator (WMM) considering holonomic and non-holonomic constraints is difficult and leads to instability of the system. The present study introduces a method of controlling the WMMs including: a general formulation, state-dependent coefficient parameterization, and control structure of the SDRE. Overcoming the problem of instability of the WMM resulted in control design for a system of cooperative manipulators mounted on a wheeled mobile platform. Optimal load distribution (OLD) was employed to distribute the load between the cooperative arms. The presence of obstacles and the probability of a collision between multiple robots in a workspace are the motivations behind employment of the artificial potential field (APF) approach. Two cooperative manipulators mounted on a mobile platform retrieved from Scout robot were modeled and simulated for situations such as controlling multiple mobile bases (collision avoidance), a cooperative system of manipulators, and moving obstacle avoidance. The OLD improved the load capacity, precision, and stability in motion of the cooperative system. Compatibility of the APF within the structure of the SDRE controller is another promising aspect of this research.     

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     

基于深度学习的四旋翼无人机单目视觉避障方法

针对无人机避障问题，提出一种基于深度学习的四旋翼无人机单目视觉避障方法。首先通过目标检测框选出目标在图像中的位置，并通过计算目标选框上下边距的长度，以此来估量出障碍物到无人机之间的距离；然后通过协同计算机判断是否执行避障动作；最后使用基于Pixhawk搭建的飞行实验平台进行实验。实验结果表明，该方法可用于无人机低速飞行条件下避障。该方法所用到的传感器只有一块单目摄像头，而且相对于传统的主动式传感器避障方法，所占用无人机的体积大幅减小。该方法鲁棒性较好，能够准确识别不同姿态的人，实现对人避障。     

一种改进的慢开始冲突避免算法研究

慢开始与拥塞避免算法及后来改进的快重传和快恢复算法是TCP拥塞控制的常用算法.虽然快重传和快恢复算法对慢开始与拥塞避免算法做了相应的改进,但其对慢开始门限的控制,一直采用乘法减小算法.当慢开始门限减至最低时,就只能以最低的慢开始门限发送数据报文.本文针对以上不足,提出一种基于网络信道拥塞状况的慢开始门限回升算法,以此达...     

汽车防撞预警系统的研究与发展

随着汽车工业的发展,汽车行驶速度越来越快,道路交通事故已成为世界性的社会问题。其中,碰撞事故占的比例约80％,所以对汽车防撞研究也成为世界性课题。先对汽车防撞预警系统的原理进行分析,再结合国内外现有的汽车防撞预警系统,如超声波防撞预警系统、雷达防撞预警系统、激光防撞预警系统、机器视觉防撞预警系统、红外线防撞预警系统以及交互式智能化防撞预警系统等,对它们的原理、特点、缺陷等方面进行分析,最后总结出现有技术的固有缺陷,提出了汽车防撞预警系统的发展方向。     

A Situation-Aware Collision Avoidance Strategy for Car-Following

In this paper, we discuss how to develop an appropriate collision avoidance strategy for car-following. This strategy aims to keep a good balance between traffic safety and efficiency while also taking into consideration the unavoidable uncertainty of position/speed perception/measurement of vehicles and other drivers. Both theoretical analysis and numerical testing results are provided to show the effectiveness of the proposed strategy.      

基于ART神经网络的机器人避碰撞系统

提出了一种基于ART神经网络的避碰撞系统(ARTCAS)。该系统采用划分区间法来描述障碍物状态,把一个全方位避碰撞问题分解为若干个区间内的避碰撞问题。结合ART神经网络学习新知识而不破坏已有知识的特点,实现了一个具有在线学习和躲避以任意速度任意角度运动的障碍物能力的避碰撞系统。     

汽车防撞系统中的危险估计与超车决策

在分析了汽车驾驶过程动态模型及制动距离模型基础之上,该文提出了基于最小安全报警距离的危险估计算法。通过对超车过程中车辆行驶的运动学分析,推导出超车所应满足的前后纵向车距求解算法。结合曲率限制,得出了超车过程完成时间的取值范围,从而实现了超车过程行使参数的决策。结合大量实验数据得到了超车安全性区域决策图,准确快捷地实现了安全决策。实验表明,本文所提出的算法实时性强,准确性高。     

An efficient system for combined route traversal and collision avoidance

Here we consider the problem of a robot that must follow a previously designated path outdoors. While the nominal path, a series of closely spaced via points, is provided with an assurance that it will lead to the destination, we can’t be guaranteed that it will be obstacle free. We present an efficient system capable of both following the path as well as being perceptive and agile enough to avoid obstacles in its way. We present a system that detects obstacles using laser ranging, as well as a layered system that continuously tracks the path, avoiding obstacles and replanning the route when necessary. The distinction of this system is that compared to the state of the art, it is minimal in sensing and computation while achieving high speeds. In this paper, we present an algorithm that is based on models of obstacle avoidance by humans and show variations of the model to deal with practical considerations. We show how the parameters of this model are automatically learned from observation of human operation and discuss limitations of the model. We then show how these models can be extended by adding online route planning and a formulation that allows for operation at varying speeds. We present experimental results from an autonomous vehicle that has operated several hundred kilometers to validate the methodology.

基于比例导引律的无人机避障研究

随着无人机作战环境日益复杂,无人机避开动态障碍物的研究成为热点问题.为提高导引避障性能,借助比例导引律的思想,通过使无人机与动态障碍物的相对速度方向导引到避障向量方向,完成避障.为满足避障完成时间和无人机机动性能约束要求,给出了避障时间估计和法向加速度表达式,通过解算得到了比例导引系数取值范围.避障完成后无人机在避障点可用比例导引律进行路径规划,最后到达目标点.仿真结果验证了算法的有效性.     

Effectiveness and driver acceptance of a semi-autonomous forward obstacle collision avoidance system

This paper proposes a semi-autonomous collision avoidance system for the prevention of collisions between vehicles and pedestrians and objects on a road. The system is designed to be compatible with the human-centered automation principle, i.e., the decision to perform a maneuver to avoid a collision is made by the driver. However, the system is partly autonomous in that it turns the steering wheel independently when the driver only applies the brake, indicating his or her intent to avoid the obstacle. With a medium-fidelity driving simulator, we conducted an experiment to investigate the effectiveness of this system for improving safety in emergency situations, as well as its acceptance by drivers. The results indicate that the system effectively improves safety in emergency situations, and the semi-autonomous characteristic of the system was found to be acceptable to drivers.     

碰撞自规避多弹分布式协同制导与控制

针对多枚导弹三维空间协同攻击机动目标情形,提出一种碰撞自规避多弹分布式协同制导律及其实现方案.基于可以测得的目标信息,将目标视作领弹,与参与协同攻击的多枚导弹形成"领弹–从弹"拓扑结构,基于网络同步算法实现导弹对目标的协同攻击.为了实现碰撞自规避,当导弹与目标相距较远时,采用带安全距离的同步算法.当导弹与目标接近时,取消该安全距离.基于运动学关系,将协同制导指令转化为速度、弹道倾角和弹道偏角指令.针对指令的跟踪控制问题,提出了一种基于改进微分器的抗干扰动态面控制方案.将参数不确定和外部扰动均视为系统干扰,采用改进微分器实现对该干扰的精确估计,从而保证了闭环系统的跟踪性能.仿真结果表明本文提出的控制器实现了对协同制导指令的精确跟踪,整个方案实现了碰撞自规避协同攻击.     

基于生物视觉的碰撞预警传感器

对拥有碰撞预警能力的小叶大运动侦察器(LGMD)神经网络进行化简,以参数化方式设计电路,网络参数可以通过串口在线配置.以此为核心设计了碰撞预警传感器,FPGA综合结果表明像素处理时钟最高可达178MHz.设计了专用测试系统进行验证,在实时模式下碰撞预警传感器根据摄像头输入正确进行碰撞预警;测试模式下用视频序列测试碰撞预警传感器,其输出膜电势与软件仿真一致,表明碰撞预警传感器继承相关软件工作的碰撞预警特性.测试系统也作为硬件加速器,加快LGMD算法运行.     

二轮小车倒立摆系统避障控制研究

二轮倒立摆小车要求其在控制摆杆稳定的同时在水平面上自由行走,对控制的时效性上提出了严格的要求.在此基础上为了实现二轮小车倒立摆的超声波避障,采用以人工势场法为主,栅格法为辅的方案实施避障.首先,根据势场法快速反应的特点迅速给出避障决策.当势场法不能准确给出正确决策的时候,采用栅格法对其做辅助决策,弥补人工势场法的不足.仿真结果表明:基于以人工势场法为主,栅格法为辅的避障方法能有效的实现二轮倒立摆小车的避障功能.