一种基于效益的多机器人避碰协调策略

多移动机器人系统在完成同时定位和地图构建SLAM任务时,机器人之间常常存在相互碰撞的问题,而这种碰撞的避免又不同于一般的避障,因为避障问题中的障碍物一般是不动的。为了解决机器人之间的避碰问题,提出了一种基于效益的多机器人避碰协调策略。该策略以提高多机器人系统探索效率为主,确定机器人通过交叉路口的顺序。同时考虑了动态协调避碰的情况,给出了确定机器人通过交叉路口顺序的算法。通过机器人在交叉路口实现避碰协调算法的仿真示例,对该方法的避碰协调过程进行了说明,并对仿真结果进行了分析,同时对仿真中机器人和目标位置的空间关系给出了合理的假设。     

3D Collision-Free Motion Based on Collision Index

A collision-free motion planning method for mobile robots moving in 3-dimensional workspace is proposed in this article. To simplify the mathematical representation and reduce the computation complexity for collision detection, objects in the workspace are modeled as ellipsoids. By means of applying a series of coordinate and scaling transformations between the robot and the obstacles in the workspace, intersection check is reduced to test whether the point representing the robot falls outside or inside the transformed ellipsoids representing the obstacles. Therefore, the requirement of the computation time for collision detection is reduced drastically in comparison with the computational geometry method, which computes a distance function of the robot segments and the obstacles. As a measurement of the possible occurrence of collision, the collision index, which is defined by projecting conceptually an ellipsoid onto a 3-dimensional Gaussian distribution contour, plays a significant role in planning the collision-free path. The method based on reinforcement learning search using the defined collision index for collision-free motion is proposed. A simulation example is given in this article to demonstrate the efficiency of the proposed method. The result shows that the mobile robot can pass through the blocking obstacles and reach the desired final position successfully after several trials.     

基于空间剖分的碰撞检测算法研究

针对虚拟环境中物体碰撞检测效率不高的问题,提出了一种基于空间剖分的碰撞检测算法。利用物体空间分布特性以及运动物体碰撞行为的局部性,先用空域分割中定性-定量结合的方法快速确定可能碰撞的物体对,再用混合层次包围盒进行精确测试,明显地提高了碰撞检测速度。实验分析表明,该算法不仅可实现复杂场景下多个物体同时发生碰撞的检测,也能保证算法在物体高速运动时的有效性。     

开放式机器人控制器中仿真组件的实现

文章将机器人三维图形仿真模块作为开放式机器人控制器中的一个通用组件来进行研究,分析了其建模和设计过程。为了保证组件的通用性,将连杆作为基本单位来设计机器人对象,并根据串联结构机器人的特点设计了通用的三维造型方法,使其可以适用于大多数串联结构的机器人。同时,为了满足机器人规划和避障的要求,在仿真组件中实现了基于距离计算的碰撞检测,并给出了仿真实验的结果。     

复杂场景中基于拓扑空间网格的碰撞检测算法

为了提高复杂场景的碰撞检测效率,提出一种基于拓扑空间网格的碰撞检测算法. 由于场景中存在众多形状复杂、尺寸不一且运动状态不同的物体,首先采取场景预处理对空间进行均匀八叉树网格划分,建立物体方向包围盒层次树与空间网格拓扑结构,利用静态大尺寸物体分割策略提升定位精确性,然后在实时检测中利用拓扑空间网格及投影相交测试排除大量不相交物体对,利用层次包围盒算法对潜在碰撞对进行精确检测并计算出碰撞点. 实验结果表明,本算法有效地提高了实时检测的效率,适用于复杂虚拟场景中的碰撞检测.     

虚拟景区中层次碰撞检测方法的研究

针对虚拟景区场景大、对象多的特点,提出了一种层次碰撞检测方法。首先运用空间剖分法过滤掉远处不可能碰撞的对象,然后再通过构建碰撞检测空间,剔除掉待测运动对象附近暂时不可能碰撞的对象,最后再运用S-AABB层次包围盒法根据每个对象的具体精度要求进行精确碰撞检测。该碰撞检测方法在满足实际精度要求的前提下,降低了碰撞检测次数和复杂度,提高了实时性,是一种针对虚拟场景高效快速的碰撞检测方法。     

基于空间扫描策略的3维相交检测算法

针对复杂虚拟场景中碰撞检测和空间分析等操作实时性差的问题,提出一种适用于3维空间对象间的快速相交检测算法——Space Sweep。该算法首先根据场景内空间对象分布特征,构建事件点及其列表;利用空间扫描策略,自适应地构建一系列假想的空间扫描面;在扫描面移动的过程中,将空间对象的状态分为死亡态、激活态和休眠态,通过只对当前处于激活态的空间对象进行相交测试,有效地减少了空间对象间不必要的相交计算。该算法提高了虚拟场景中3维空间对象间相交检测的效率,为3D GIS中实时空间分析提供了有力的技术支持。最后,通过对比测试验证了本文算法的实用性。     

基于VR的二维触发式碰撞检测算法

在虚拟场景中经常会用到虚拟现实技术设置某精灵的移动范围和区域, 物体与物体之间碰撞检测的算法成为技术关键, 常用的基于图形图像的算法虽然很有效应用范围广, 但是无事件处理能力, 并且执行效率低和占用大量的系统资源. 本文介绍一种利用二维数组高效的碰撞检测算法, 满足执行效率高但精度要求不高的碰撞检测.     

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     

Real-time Velocity Alteration Strategy for Collision-free Trajectory Planning of Two Articulated Robot Manipulators

Two articulated robots working in a shared workspace can be programmed by planning the tip trajectory of each robot independently. To account for collision avoidance between links, a real-time velocity alteration strategy based on fast and accurate collision detection is proposed in this paper to determine the step of next motion of slave (low priority) robot for collision-free trajectory planning of two robots with priorities. The effectiveness of the method depends largely on a newly developed method of accurate estimate of distance between links. By using the enclosing and enclosed ellipsoids representations of polyhedral models of links of robots, the minimum distance estimate and collision detection between the links can be performed more efficiently and accurately. The proposed strategy is implemented in an environment where the geometric paths of robots are pre-planned and the preprogrammed velocities are piecewise constant but adjustable. Under the control of the proposed strategy, the master robot always moves at a constant speed. The slave robot moves at the selected velocity, selected by a tradeoff between collision trend index and velocity reduction in one collision checking time, to keep moving as far as possible and as fast as possible while avoid possible collisions along the path. The collision trend index is a fusion of distance and relative velocity between links of two robots to reflect the possibility of collision at present and in the future. Graphic simulations of two PUMA560 robot arms working in common workspace but with independent goals are conducted. Simulations demonstrate the collision avoidance capability of the proposed approach as compared to the approach based on bounding volumes. It shows that advantage of our approach is less number of speed alterations required to react to potential collisions.     

基于运动对象局部场景截取的碰撞检测算法

为了解决虚拟心脏介入手术系统中的碰撞检测问题,提出了一种基于运动对象局部场景截取的碰撞检测算法.通过实时构建运动对象的局部场景截取体,可以获取该对象周围的局部场景数据,有效地降低了碰撞检测复杂性.并且它对虚拟场景中埘象的形变属性没有特殊要求,可适用于虚拟环境中包含可形变对象的情形.通过虚拟心脏介入手术中的碰撞检测实验表明,碰撞检测频率达到500Hz以上,并能精确给出碰撞点和发生碰撞的基本几何元素等碰撞信息,可以满足虚拟心脏介入手术对碰撞检测的实时性与精确性要求.     

SLAMMOT-SP: Simultaneous SLAMMOT and Scene Prediction

In recent years, SLAMMOT (simultaneous localization, mapping and moving object tracking) has attracted widespread attention in the mobile robot field. This paper proposes a new approach, SLAMMOT-SP, which combines SLAMMOT and scene prediction (SP). It extends the SLAMMOT problem to simultaneous map prediction and moving object trajectory prediction. The robot not only passively collects the data and executes SLAMMOT, but actively predicts the scene. The recursive Bayesian formulation of SLAMMOT-SP is derived for real-time operations. A generalized framework for tracking and predicting the moving objects is also proposed. Simulations and experiments show that the proposed SLAMMOT-SP is effective and can be performed in real-time.     

VISYR: a simulation tool for mobile robots using vision sensors

With the advent of mobile robots and inboard vision sensors mounted directly on the robot's wrist, new kinds of problems lie in the image processing field as, for example, dynamic scene analysis or motion estimation. The lack of flexibility of real experiments led us to implement at IRISA a general simulation tool devoted to the study of robots using moving vision sensors. VISYR allows us to simulate the image perceived by a robot of its environment during its motion.The first part of the paper is devoted to the modelling of the 3D scene containing complex objects and to the design of a suitable robotics vision sensor. In the second part, a new algorithm of dynamic management of the local data basis perceived by the sensor is presented. The parameters of the vision sensors are highly adjustable and VISYR is conceived to allow the fast development of algorithms using dynamic vision data.     

Adaptive dynamic collision checking for single and multiple articulated robots in complex environments

Static collision checking amounts to testing a given configuration of objects for overlaps. In contrast, the goal of dynamic checking is to determine whether all configurations along a continuous path are collision-free. While there exist effective methods for static collision detection, dynamic checking still lacks methods that are both reliable and efficient. A common approach is to sample paths at some fixed, prespecified resolution and statically test each sampled configuration. But this approach is not guaranteed to detect collision whenever one occurs, and trying to increase its reliability by refining the sampling resolution along the entire path results in slow checking. This paper introduces a new method for testing path segments in c-space or collections of such segments, that is both reliable and efficient. This method locally adjusts the sampling resolution by comparing lower bounds on distances between objects in relative motion with upper bounds on lengths of curves traced by points of these moving objects. Several additional techniques and heuristics increase the checker's efficiency in scenarios with many moving objects (e.g., articulated arms and/or multiple robots) and high geometric complexity. The new method is general, but particularly well suited for use in probabilistic roadmap (PRM) planners, where it is critical to determine as quickly as possible whether given path segments collide, or not. Extensive tests, in particular on randomly generated path segments and on multisegment paths produced by PRM planners, show that the new method compares favorably with a fixed-resolution approach at "suitable" resolution, with the enormous advantage that it never fails to detect collision.     

多机器人体间动态碰撞检测方法仿真研究

当前多结合包围求碰撞检测法、Average-Case法、K-DOPs法等实现多机器人体间动态碰撞的检测,均存在寻优性能较差、检测效率较低的问题。为此提出一种基于动态粒子群的多机器人体间动态碰撞检测方法。采用OBB层次包围盒方法,缩小多机器人之间需要动态碰撞检测的区域,同时把动态碰撞检测问题转换为物体特征对间距离机制的非线性优化问题,进而构建层次拓扑框架进行局部碰撞检测,将机器人体引入到粒子群算法中建立混合进化算法,找到动态碰撞检测的最优解,实现多机器人体间动态碰撞检测。仿真结果证明,所提方法的检测效率高达96%,且具有较高的寻优性能。     

Indoor scene recognition by a mobile robot through adaptive object detection

Mobile robotics has achieved notable progress, however, to increase the complexity of the tasks that mobile robots can perform in natural environments, we need to provide them with a greater semantic understanding of their surrounding. In particular, identifying indoor scenes, such as an Office or a Kitchen, is a highly valuable perceptual ability for an indoor mobile robot, and in this paper we propose a new technique to achieve this goal. As a distinguishing feature, we use common objects, such as Doors or furniture, as a key intermediate representation to recognize indoor scenes. We frame our method as a generative probabilistic hierarchical model, where we use object category classifiers to associate low-level visual features to objects, and contextual relations to associate objects to scenes. The inherent semantic interpretation of common objects allows us to use rich sources of online data to populate the probabilistic terms of our model. In contrast to alternative computer vision based methods, we boost performance by exploiting the embedded and dynamic nature of a mobile robot. In particular, we increase detection accuracy and efficiency by using a 3D range sensor that allows us to implement a focus of attention mechanism based on geometric and structural information. Furthermore, we use concepts from information theory to propose an adaptive scheme that limits computational load by selectively guiding the search for informative objects. The operation of this scheme is facilitated by the dynamic nature of a mobile robot that is constantly changing its field of view. We test our approach using real data captured by a mobile robot navigating in Office and home environments. Our results indicate that the proposed approach outperforms several state-of-the-art techniques for scene recognition.     

On the Recognition and Location of Partially Occluded Objects

The recognition and location of partially occluded objects is important for image-guided robot automation. A computational object recognition system consists of three main parts: shape representation, matching strategies and verification. The shape representation scheme, which is always application-oriented, should keep extracted features as invariant as possible. This paper presents a new model-based object recognition scheme for general two dimensional objects in a cluttered scene. The scheme considers objects subjected to similarity transformations (i.e., a combination of rotation, scaling and translation). It employs a new feature detection algorithm, combining curvature measures and polygonal approximation. An approximate, but efficient matching strategy is proposed for hypothesis generation and synthetic verification procedures are introduced to improve the robustness of the system. Experiment results are presented to show that the system works effectively and efficiently.     

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.     

基于空间划分和线性规划的快速碰撞检测算法

为提高在复杂环境下多物体碰撞检测的速度,提出基于空间划分和线性规划的快速碰撞检测算法。该算法首先用均匀网格法来确定处于同一单元格内的对象,然后利用线性规划的方法对处于同一单元格内的对象进行精确测试,并实时得到碰撞检测的结果。实验结果表明,与传统的碰撞检测算法相比,该算法可以缩短计算时间,提高了碰撞检测的效率。     

机器人带未知负载条件下的碰撞检测算法

未知负载会增大机器人模型误差，对碰撞检测产生严重干扰，甚至导致算法失效．为此，本文提出了一种适用于机器人带负载工作情况的碰撞检测算法．首先，基于机器人广义动量设计具有带通滤波特性的新型力矩观测器，通过对机器人动力学频域特性进行分析，得到机器人动力学模型与关节运行速度对应的最大频率阈值，确定带通力矩观测器的参数．然后，利用带通力矩观测器对关节力矩信号进行滤波，提高碰撞检测算法对机器人模型误差的容忍度．最后，通过人与机器人交互实验进一步验证了该碰撞检测算法的有效性．实验结果表明，该算法与已有的算法相比具有更好的鲁棒性，可满足机器人带未知负载0～2 kg的工作需求．