Issues in autonomous navigation of underground vehicles

This paper describes current research at the Australian Centre for Field Robotics (ACFR) in collaboration with the Commonwealth Scientific and Industrial Research Organisation (CSIRO) within the Cooperative Research Centre (CRC) for Mining Technology and Equipment (CMTE) towards achieving autonomous navigation of underground vehicles, like a Load-Haul-Dump (LHD) truck. This work is being sponsored by the mining industry through the Australian Mineral Industries Research Association Limited (AMIRA). Robust and reliable autonomous navigation can only be realised by achieving high level tasks such as path-planning and obstacle avoidance. This requires determining the pose (position and orientation) of the vehicle at all times. A minimal infrastructure localisation algorithm that has been developed for this purpose is outlined and the corresponding results are presented. Further research issues that are under investigation are also outlined briefly.

Evaluation of cooperative exploration strategies using full system simulation

This paper compares different state-of-the-art exploration strategies for teams of mobile robots exploring an unknown environment. The goal is to help in determining a best strategy for a given multi-robot scenario and optimization target. Experiments are done in a 2D-simulation environment with 5 robots that are equipped with a horizontal laser range finder. Required components like SLAM, path planning and obstacle avoidance of every robot are included in a full-system simulation. To evaluate different strategies the time to finish exploration, the number of measurements that have been integrated into the map and the development in size of the explored area over time are used. The results of extensive test runs on three environments with different characteristics show that simple strategies can perform fairly well in many situations but specialized strategies can improve performance with regards to their targeted evaluation measure.

空间机械臂在线实时避障路径规划研究

针对目前空间机械臂避障路径规划算法计算量大难以达到在线实时规划的缺点,对空间机械臂的在线实时避障路径规划问题进行了研究和探讨.采用规则体的包络对障碍物进行建模,并借助C空间法的思想,把障碍物和机械臂映射到两个相互垂直的平面内,将机械臂工作空间的三维问题转化为二维问题,并结合二岔树逆向寻优的方法进行路径搜索,从而大大减少了计算量,达到了在线实时规划的要求.最后在空间机器人仿真系统上对其进行了仿真研究,验证了该方法的可行性.

Convex model predictive control for vehicular systems

In this work, the author presents a method called Convex Model Predictive Control (CMPC) to control systems whose states are elements of the rotation matrices SO(n) for n = 2, 3. This is done without charts or any local linearization, and instead is performed by operating over the orbitope of rotation matrices. This results in a novel model predictive control (MPC) scheme without the drawbacks associated with conventional linearization techniques such as slow computation time and local minima. Of particular emphasis is the application to aeronautical and vehicular systems, wherein the method removes many of the trigonometric terms associated with these systems’ state space equations. Furthermore, the method is shown to be compatible with many existing variants of MPC, including obstacle avoidance via Mixed Integer Linear Programming (MILP).

SCARA errobota: mugimendu gaitasunen eta ibilbide sorkuntzaren inplementazioa software grafikoan

[EU]Lan honen gaia SCARA errobot motaren mugimendu gaitasunen analisia egitea da, eta ibilbideen sorkuntzarako metodoekin batera software grafiko batean inplementatzea mugimenduaren simulazioa egin ahal izateko. Errobot serieen zinematikaren oinarrizko ezagutzatik hasita, mota konkretu batetara aplikatu egiten da eta honek aurkezten dituen berezitasunak garatu egiten dira, bi helburutara bideratuta: SCARA errobotaren mugimendu gaitasunak ezagutzea. Ibilbideen sorkuntzarako metodo baten inplementazioa. Hasteko, gaiaren egoera aztertu da, aplikazio nagusien eta ibilbide moten informazioa batzeko. Halaber ibilbideen sorkuntzarako metodoak arakatu dira, erabilera honetarako aproposena aurkitzeko. Jarraian, errobotaren analisia burutu da, ohizko erreminta matematikoak erabiliz, funtsezkoak diren lan eremua eta kokapen singularrak lortzeko. Ostean, software grafikoa garatu da mugimendu gaitasun hauek simulatzeko. Ohiko aplikazioetan oinarritutako ibilbideak sortzeko aukerak gehitu dira. Amaitzeko, oztopoak saihesten dituen ibilbideen sorkuntzarako metodoa inplementatu da, “pick and place” ibilbide motaren barruan.

Biologically inspired visual odometer for navigation of a flying robot

Experimental research in biology has uncovered a number of different ways in which flying insects use cues derived from optical flow for navigational purposes, such as safe landing, obstacle avoidance and dead reckoning. In this study, we use a synthetic methodology to gain additional insights into the navigation behavior of bees. Specifically, we focus on the mechanisms of course stabilization behavior and visually mediated odometer by using a biological model of motion detector for the purpose of long-range goal-directed navigation in 3D environment. The performance tests of the proposed navigation method are conducted by using a blimp-type flying robot platform in uncontrolled indoor environments. The result shows that the proposed mechanism can be used for goal-directed navigation. Further analysis is also conducted in order to enhance the navigation performance of autonomous aerial vehicles. © 2003 Elsevier B.V. All rights reserved.

一种移动机器人在三维动态环境下的路径规划方法

提出一种基于遗传算法的三维动态环境下的路径规划方法,通过对机器人的运动行为进行编码,将各种约束条件融入到遗传算法当中,规划出可实际应用的避障路径,仿真研究表明该方法是简单有效的。

动态多障碍物环境下目标追踪的路径规划方法

采用人工势场(AP)引导进化算法(EA)的搜索方法解决了动态多障碍物环境下的目标追踪问题.把人工势场与FA搜索相结合进行动态路径规划,使搜索沿着势场方向进行,得到一条相对于搜索区域最优的轨迹.以单车、单运动目标,有多个运动障碍物存在的情况为例,通过仿真试验对AP引导EA和单纯EA两种搜索方法的性能进行了比较,说明了AP引导EA搜索方法在处理动态多运动障碍物问题时相对传统EA方法具有实时、高效、收敛的特点,同时在很大程度上解决了单纯AP方法在解决多障碍物问题时的局部极小问题。

非完整自主车基于圆轨迹的道路避障

本文就四轮非完整自主车提出了一种基于圆轨迹的道路避障策略。先将道路上的障碍按照障碍距离自主车的远近划分层次,使一个层次的障碍能在自主车视场中全部出现。然后给出基于圆轨迹的避障算法,即自主车沿由自主车出发位姿和子目标点确定的圆弧轨迹走行。在此之前推导四轮非完整车的运动模型为提出避障策略的基础准备。尽量减小自主车在走行过程中运动状态的改变,基于圆轨迹避障策略能够很好地满足这一要求。最后引入代价函数,给出对于此方法的评价,体现了本方法的优越性。

冗余自由度机械手的避障控制

避障碍物一直是冗余自由度机械手的主要应用 ,本文采用伪逆矩阵法 ,以障碍物和机械手之间的距离的函数作为性能指标函数来解冗余自由度机械手逆解 ,进行避障控制 ,并提出一种简单的计算机械手和障碍物之间的距离方法 ,通过对一个三自由度的平面机械手进行仿真 ,验证了算法的正确性

移动机器人的障碍物群检测方法

利用激光和超声波传感器在用栅格表示法形成地图的基础上 ,提出了进行数据融合以提取环境特征的新方法 :识别障碍物群。该方法能够在密集障碍物环境中为机器人的路径规划和避障提供准确的环境特征信息 ,提高机器人系统的自主性和实时性。实验结果表明了该方法的有效性。

一种欠驱动AUV的三维实时避碰方法

针对以测距声纳为避碰传感器的一类欠驱动型AUV，提出了一种水平面和垂直面相结合的三维实时避碰方法。根据测距声纳和欠驱动AUV 的特殊性，首先从运动规划和路径规划2 个层次提出了AUV 混合型实时避碰结构，并分别设计了基于事件反馈监控的避碰自动机和基于免疫遗传的局部路径规划算法。多种典型障碍场景的半物理仿真实验表明，论文所提方法能够实现AUV 安全、稳定的三维避碰过程。

一种自治水下机器人垂直面避碰规划方法

为提高自治水下机器人在垂直面跨越坡型、台阶型障碍的能力,提出了一种基于模糊控制的垂直面避碰规划方法。该方法以避碰声纳的输出作为输入,垂直面的深度调节量作为输出,直接建立了从障碍感知到避碰行为的映射。半物理仿真实验表明,该方法有效提高了某型自治水下机器人垂直面操纵性能,具有反应迅速、稳定性好、便于工程实现的优点。

一种海底地形和海流虚拟生成方法

提出了一种用于AUV视景仿真的海洋环境中海底地形和海流的虚拟实现方法。海底地形不但考虑了离散点电子海图数据,而且也将某些特征数据考虑在内,从而生成相对精度较高的海底地形。海洋中的海流采用两个层次的方法进行模拟:建立海流数据库方法以及水动力软件计算方法。该方法的研究对于AUV自主地形导航技术以及避碰策略等研究具有极为重要的意义,并且上述方法生成的海洋环境已经在AUV数字仿真平台中得到了应用。

远程自治水下机器人三维实时避障方法研究

海洋环境通常是不确定、非结构化和未知的 ,而远程AUV(LAUV)的避障声纳对环境感知有一定的局限 ,因此很难建立起精确、完整和统一的三维环境模型 .LAUV实时避障是一个实时性很强的动态过程 ,它不但与环境有关 ,而且还与LAUV的运动学约束、动力学特性和操纵性有关 .针对上述问题本文提出了一种基于复合控制的三维实时模糊避障方法