机械外文文献翻译-无人驾驶电动铲越障车【中文2578字】【PDF+中文WORD】

机械外文文献翻译-无人驾驶电动铲越障车【中文2578字】【PDF+中文WORD】,中文2578字,PDF+中文WORD,机械,外文,文献,翻译,无人驾驶,电动,越障,中文,2578,PDF,WORD 无人驾驶电动铲越障车 摘要 在自然灾害发生后会产生大量的废墟，阻碍了救援人员解救被困人员，延缓了救灾行动。动力铲通常用来清理废墟残骸，但这个过程可能需要很多时间。此外，在这种不稳定的条件下，让救援人员操作重型机械是非常危险的。为了加快进入被困人员区域，可以通过灵活机动的无人驾驶动力铲臂来执行，而不是将其淘汰，在这项工作中，无人驾驶动力铲的自主障碍技术是至关重要的。在不同的序列中，优化总能量消耗的方法被选为克服给定步骤障碍的最佳方法，动态仿真结果表明了该方法的有效性。 关键词:动力铲；障碍超越；无人驾驶；优化 背景 每年世界上许多国家都受到地震、洪水、台风等自然灾害的侵袭，这些灾害不仅造成生命损失，而且它们也会产生大量的废墟，这导致了搜索和救援任务缓慢及救援困难度加大。在受灾地区，让人们操作动力铲操作清理废墟，是一项危险的任务，因为这些机器有可能因安装的不稳定而发生故障，对人们造成伤害。此外，清除所有的障碍并最终进入内部区域需要花费大量的时间。 为了加快救援行动的速度，越过巨大的障碍物，而不是清除它们，这时使用履带轮，动力铁锹能有效地解决这一问题。然而，在使用动力铲的情况下，有几个难题需要克服:只有在履带车的爬坡范围内的障碍物才能被克服;履带越障车的力量可以很容易的饱和;当它处于障碍物的顶部时，如果没有灵巧地移动，它可以翻倒并损坏自己。作为重型机械，在翻倒的时候，动力铲也很难回到原来的状态。 以前在挖掘机上的工作可以在[2-5]找到。参考文献[2]提出了一种挖掘器的动态模型，目的是开发一个用于地面、月球和行星挖掘的自动挖掘控制系统。[3]详细研究了具有液压执行机构的挖掘机的运动学。参考文献[4]主要集中在一个完全自动化卡车装载任务的系统上。在这个系统中，挖掘机的软件决定了在哪里挖掘，在哪里倾倒卡车，以及如何快速在这些点之间移动，同时检测和停止障碍物。研究了开挖过程的性质和控制方法，并在[5]中进行了自动开挖的目的。 在其他相关的工作中，一种自动爬楼梯的履带机器人被引入[6]。但是，它不使用任何武器援助。参考文献[7]介绍了一种救援机器人的试验系统，该系统允许人类操作员在三维碎片环境中提出正确的方向。相比之下，拟议的sys- tem则寻求无需人工干预的自动操作。参考文献[8]提出了一种可移动的质心(CoM)的轮式机器人，以方便在崎岖的地形上行走。拟议的系统也考虑通过操纵它的手臂来间接地改变CoM;如何-永远，主要的焦点是在桶中得到反应力作为支撑来举起动力铲履带。 Fig. 1 Basic parts of a power shovel. The coordinate frame convention is X forward, Y left and Z up X (forward) crawler step platform boom joint power shovel bucket bucket joint axis of platform rotation boom arm Z (up) arm joint 问题陈述 如果有一个类似阶梯状的障碍物，动力铲应该机动它的手臂以平稳的轨迹爬上障碍物。此外，它还应该以这样一种方式进行机动，使总能量消耗降到最低。整个过程是自动化的，这样就消除了人类工人的风险。 b stage 2 Fig. 2 Obstacle surmount stages. The power shovel with dotted lines depicts the initial state while the the one with the regular lines depicts the final state for each stage. P1, P2, P3 and αF denote the parameters of the total maneuver. B and E denote bucket and step edge positions respectively B P3 E initial pose of stage 2 Pb P4 step Pb : bottom center position final pose of stage 2 αF P1 a stage 1 E initial pose of stage 1 Pb Pb : bottom center position P2 step B final pose of stage 1 方法 在提出的方法中，障碍超越操作分为两个阶段。在第一阶段，铲斗保持在动力铲的前部，并提供所需的反作用力，使爬虫的正面向上爬升到阶梯状结构;爬虫的尾部保持与地面水平的接触。如图2a所示。第一阶段完成后,平台旋转180°boom-arm-bucket复合移动到后面的电铲启动第二阶段。与第一阶段类似，吊桶提供了所需的反作用力，以提升爬虫的尾部，完成第2阶段的全部surmount操作。如图2b所示。在第一和第二阶段，水桶保持固定的地面位置，使用摩擦力[1]或由斗齿锚定，这是稳定机动的支点;可根据环境选择适合的锚固方法。 讨论 可以看出，CFSQP结果与完全慢批量模拟得到的结果比较好。事实上，CFSQP已经捕获了目标函数(能量)的连续性质，因此能够获得最高效的param- eters，即使在基于较小参数的情况下，也不能被捕获。从CFSQP的能量结果来看，这是明显的，比彻底的慢批量模拟的结果要小。为了使CFSQP运行，必须将修改包含到原始算法中。也就是说，当目标函数的梯度是有限的。 差分逼近,算法倾向于使用附近的点,甚至可以违反给定con -制度化。这可能会导致ODE崩溃，因为输入的定义不明确。为了克服这个问题，在测试不确定的点时注入了大量的成本。 吊杆、臂和桶接头的关节轨迹(图11、12、13)确认关节平稳过渡。然而，每个数字的不连续性需要特别的说明。第一阶段完成后，平台旋转到动力铲的背面开始第二阶段。假设这个简单的操作可以通过恒定的能量来完成，因此为了简单起见，我们省略了分析。因此，由于序列1和序列2-1之间的最终和初始关节的不匹配，可以看到间断。 参数P4被认为是常量。 模拟。P4的唯一要求是，当2-2序列完成后，电铲在提升吊桶后能够保持稳定。在此之前，只要满足这一要求，P4就可以被设定为一个经验值，而不被包含在优化过程中。 open dynamics engine (ODE)[9]包括两个默认求解器，即(1)Dantzig的agm solver。 (2)连续超松弛(SOR)投影高斯- Seidel (PGS) LCP求解器。在这个工作中，Dantzig的agm solver已经被用于实现a。 数值精确解，即使它大约是一个数量级的慢于或PGS LCP求解器。 从图14可以看出，关节突在不同的阶段经历一定的瞬态。在第一阶段的开始阶段，由于两个原因导致转矩瞬变:(1)履带前的接触与地面接触，(2)当桶开始推台阶或地面时产生的内力。类似的情况出现在第二阶段的开始阶段，爬虫的背部(但由于平台旋转而被视为爬虫的前部)开始向上移动并与地面失去联系。另一个重要的观察是重力条件(每一个连杆的质量)在其他术语上占主导地位，比如科里奥利力、向心和惯性项，因为它们的关节速度和加速度相对较小。 作为障碍物的第一步，将一个类似于sim的阶梯状结构作为障碍物。如何——永远不要忘记，使用它的手臂和水桶来改变地形是有好处的。其结果是，它可以将非结构化的地形铺在前面，利用台阶切割法等快速方法将其塑造成阶梯状结构，并采用所提出的方法;将地形完全修改成光滑的边坡需要相当长的时间，这就否定了原来的目的。 未来的工作 提出的方法是解决这一问题的第一步，因此选择了一个简单的阶梯状障碍物。由于问题的对称性，在模拟中可以忽略y坐标运动。此外，臂和桶连接轴相互平行，这使得cor-响应的连接在飞机上移动。这也使我们将三维运动简化为二维空间。然而，在自然灾害之后产生的碎片有非常复杂的形状。作者希望在未来解决各种障碍的问题，这就需要对全三维运动进行分析。克服复杂障碍的另一个方面是稳定性问题。电铲在整个操作过程中应保持其稳定性，在任何情况下都不应倾斜。 在轨迹规划中采用简单的高阶多项式，因为它简单易用，没有遇到任何问题。然而，spline(分段连续多项式)在轨迹规划中得到了popu- larity，作者希望通过将简单的多项式在未来改变为样条函数来观察其改进。 作为下一步，作者希望在未来使用真实的硬件进行扩展，以确认通过模拟获得的结果。 5 Surmounting obstacles by arm maneuver for unmanned power shovel Abstract Large debris created after natural disasters restrict access to inner parts of affected regions, and slows down disaster relief operations. Power shovels are often used to clear wreckage but the process can take a lot of time. Moreover, it is dangerous to involve human workers operating heavy machinery in such unstable conditions. To speedup access to inner areas, obstacles can be surmounted with the assistance of carefully maneuvered power shovel arm, instead of removing them. In this work, an autonomous obstacle surmounting technique for an unmanned power shovel is proposed. Out of different sequences, the one that optimizes the total energy consumption is chosen as the best can- didate for surmounting a given step-like obstacle. Dynamic simulation results show the effectiveness of the proposed method. Background Each year many countries in the world are challenged by natural disasters such as earthquakes, floods, tsu- namis, typhoons and so on. While these disasters can cause loss of life, they also generate large amounts of debris, which further reduces access to inner parts of the affected regions. This results in slowing down of search and rescue missions as well as other disaster relief opera- tions. Power shovels are used in disaster stricken areas to remove wreckage and to clear up roads. Neverthe- less, it is a dangerous task to involve human workers to operate such heavy machines in these conditions as there is chance of tip over of these machines due to instabil- ity. Moreover, it can take a lot of time to clear up all the obstacles and finally get access to inner areas. In order to speed up disaster relief operations, large obstacles can be surmounted instead of clearing them. Using crawler wheels, power shovels have the ability to go over objects effectively compared to other vehi- cles. However, there exists several challenges to obsta- cle surmounting with power shovels as follows: only theobstacles that are within the climbing limit of the crawler can be overcome; crawler power can be easily saturated; power shovel can tip over and damage itself if not moved skillfully when it is on top of an obstacle; being heavy machines, power shovels are also difficult to get back to the original state at the event of tip over. To overcome the aforementioned problems, a power shovel can maneuver its arm effectively to assist the obstacle surmount operation. In fact, such arm assistance is being used nowadays to load small power shovels to trucks for transportation. As can be seen on [1], it can be achieved only with great level of skill and competency. Considering this scenario as a starting point, this work presents an autonomous arm maneuver based obstacle surmounting method to overcome a step-like structure for an unmanned power shovel (Fig. 1). Among different maneuver sequences, the best maneuver is chosen based on the minimum total energy consumption. Further- more, a smooth trajectory of the machine is preferred to avoid any vibrations and jerk exerted on itself and on its surroundings. Previous works on excavators can be found at [2–5]. Ref. [2] presents a dynamic model for an excavator with the intention of developing an automated excavation con- trol system for terrestrial, lunar, and planetary excavation. The kinematics of excavators having hydraulic actuatorsare investigated in detail in [3]. Ref. [4] mainly focuses on a system that completely automates the truck loading task. In that system the excavator’s software decides where to dig in the soil, where to dump in the truck, and how to quickly move between these points while detecting and stopping for obstacles. The nature of an excavation process and the way it may be controlled is investigated with the intention of automatic excavation in [5]. Among other related works, an autonomous stair- case climbing tracked mobile robot is introduced in [6]. However, it does not use any arms for assistance. Ref. [7] introduces a pilot system for a rescue robot to let a human operator suggest good directions to traverse on a 3D debris environment. In contrast, the proposed sys- tem seeks autonomous operation without any human intervention. Ref. [8] has proposed a wheeled robot with a movable center of mass (CoM) to ease the traverse over rough terrain. The proposed system also considers change of CoM, indirectly, by maneuvering its arm; how- ever, the main focus is on getting the reaction force at the bucket as a support to lift the power shovel crawler. Fig. 1 Basic parts of a power shovel. The coordinate frame convention is X forward, Y left and Z up X (forward) crawler step platform boom joint power shovel bucket bucket joint axis of platform rotation boom arm Z (up) arm joint Problem statement Given a step-like obstacle, the power shovel should maneuver its arm to climb up the obstacle in a smooth trajectory. Also, it should carry out the maneuver in such a way that the total energy consumption is minimized. The whole process is to be automated so that the risk for the human workers is eliminated. Nomenclature The basic parts of a power shovel are illustrated in Fig. 1; boom, arm and bucket are the main links considered, while each link is attached to the previous link by boom- joint, arm-joint and bucket-joint, respectively. These joints are individually controlled to achieve different poses similar to a serial link robot manipulator. There is a rotating platform, which can rotate around its local z axis (vertical) so that the whole boom-arm-bucket composite can be moved to its front and back, symmetrically. The vehicle stands on a crawler that provides better mobility on unstructured terrain. Methods b stage 2 Fig. 2 Obstacle surmount stages. The power shovel with dotted lines depicts the initial state while the the one with the regular lines depicts the final state for each stage. P1, P2, P3 and αF denote the parameters of the total maneuver. B and E denote bucket and step edge positions respectively B P3 E initial pose of stage 2 Pb P4 step Pb : bottom center position final pose of stage 2 αF P1 a stage 1 E initial pose of stage 1 Pb Pb : bottom center position P2 step B final pose of stage 1 In the proposed method the obstacle surmount operation is divided into two stages. In the 1st stage, the bucket is kept at the front of the power shovel and it provides the required reaction force to lift the front of the crawler to climb up the step-like structure; the rear of the crawler maintains contact with the ground level. This is illus- trated in Fig. 2a. After the 1st stage is completed, the platform rotates 180° to move the boom-arm-bucket composite to the back of the power shovel to initiate the 2nd stage. Similar to the 1st stage, the bucket provides the required reaction force to lift the rear of the crawler to complete the total surmount operation in the 2nd stage. This is illustrated in Fig. 2b. Throughout 1st and 2nd stages, the bucket maintains fixed ground position either by using friction force [1] or anchored by bucket teeth, which acts as a pivot for stable maneuver; the suit- able anchoring method can be chosen depending on the environment. Discussion It can be observed that the CFSQP result compare well with the result obtained in the exhaustive slow batch simulation. In fact, CFSQP had captured the continuous nature of the objective function (energy) and as a result had been able to obtain the most energy efficient param- eters, which cannot be seized even when exhaustive batch simulations are run based on smaller parameter incre- ments. This is evident from CFSQP energy result being smaller than that of the exhaustive slow batch simulations. To make CFSQP running, a modification had to be included into the original algorithm. That is, when the gradient of the objective function is calculated by finite Angle [deg] difference approximation, the algorithm tends to use nearby points, which can even violate the given con- straints. This can make ODE crash due to ill-defined inputs. To overcome this problem, a large cost was injected when ill-defined points were tested. The joint trajectories for boom, arm and bucket joints (Figs. 11, 12, 13) confirm that the joints undergo smooth transition. However, the discontinuity of each figure needs special mention. After the 1st stage has finished the platform rotates to the back of the power shovel to start the 2nd stage. It is assumed that this trivial operation can be done by constant energy and therefore omitted from the analysis for simplicity. As a result, a discontinuity can be seen due to the mismatch of final and initial joint posi- tions between sequence 1 and sequence 2–1. The parameter P4 is considered to be constant in thesimulation. The only requirement for P4 is such that the power shovel should be able to maintain stability once it lifts the bucket after sequence 2–2 is completed. There- fore, as long as this requirement is fulfilled, P4 can be set to an empirical value and not be included in the optimi- zation process. The open dynamics engine (ODE) [9] consists of two default solvers namely, (1) Dantzig’s Agorithm solver, and(2) Successive Over-Relaxation (SOR) Projected Gauss- Seidel (PGS) LCP solver. Dantzig’s Agorithm solver has been used in this work as it attempts to achieve anumerically exact solution, even though it is about one order of magnitude slower than SOR PGS LCP solver. From Fig. 14, it can be observed that the joint tor- ques undergo certain transients at different stages. At the beginning of 1st stage, torque transients occur due to two reasons: (1) front of the crawler looses the contact with ground, and (2) internal forces generated when the bucket starts pushing the step or ground. A similar condition occurs at the beginning of the 2nd stage where the back of the crawler (however, seen as the front of the crawler due to platform rotation) starts moving upwards and looses contact with the ground. Another important observation is that the gravity terms (mass of each link) have dominated over other terms such as Coriolis, centripetal and inertial terms because of the relatively small joint velocities and accelerations. As the first step of obstacle surmount operation a sim- ple step-like structure was chosen as the obstacle. How- ever, one should not forget that power shovels have the advantage of modifying the terrain using its arm and bucket. As a result, it can pave the unstructured terrain in front of it to shape it to a step-like structure using fast methods like bench cut method and employ the proposed method; totally modifying the terrain into a smooth slope would take a considerable amount of time, which negates the original purpose.  无人驾驶电动铲越障车 摘要 在自然灾害发生后会产生大量的废墟，阻碍了救援人员解救被困人员，延缓了救灾行动。动力铲通常用来清理废墟残骸，但这个过程可能需要很多时间。此外，在这种不稳定的条件下，让救援人员操作重型机械是非常危险的。为了加快进入被困人员区域，可以通过灵活机动的无人驾驶动力铲臂来执行，而不是将其淘汰，在这项工作中，无人驾驶动力铲的自主障碍技术是至关重要的。在不同的序列中，优化总能量消耗的方法被选为克服给定步骤障碍的最佳方法，动态仿真结果表明了该方法的有效性。 关键词:动力铲；障碍超越；无人驾驶；优化 背景 每年世界上许多国家都受到地震、洪水、台风等自然灾害的侵袭，这些灾害不仅造成生命损失，而且它们也会产生大量的废墟，这导致了搜索和救援任务缓慢及救援困难度加大。在受灾地区，让人们操作动力铲操作清理废墟，是一项危险的任务，因为这些机器有可能因安装的不稳定而发生故障，对人们造成伤害。此外，清除所有的障碍并最终进入内部区域需要花费大量的时间。 为了加快救援行动的速度，越过巨大的障碍物，而不是清除它们，这时使用履带轮，动力铁锹能有效地解决这一问题。然而，在使用动力铲的情况下，有几个难题需要克服:只有在履带车的爬坡范围内的障碍物才能被克服;履带越障车的力量可以很容易的饱和;当它处于障碍物的顶部时，如果没有灵巧地移动，它可以翻倒并损坏自己。作为重型机械，在翻倒的时候，动力铲也很难回到原来的状态。 以前在挖掘机上的工作可以在[2-5]找到。参考文献[2]提出了一种挖掘器的动态模型，目的是开发一个用于地面、月球和行星挖掘的自动挖掘控制系统。[3]详细研究了具有液压执行机构的挖掘机的运动学。参考文献[4]主要集中在一个完全自动化卡车装载任务的系统上。在这个系统中，挖掘机的软件决定了在哪里挖掘，在哪里倾倒卡车，以及如何快速在这些点之间移动，同时检测和停止障碍物。研究了开挖过程的性质和控制方法，并在[5]中进行了自动开挖的目的。 在其他相关的工作中，一种自动爬楼梯的履带机器人被引入[6]。但是，它不使用任何武器援助。参考文献[7]介绍了一种救援机器人的试验系统，该系统允许人类操作员在三维碎片环境中提出正确的方向。相比之下，拟议的sys- tem则寻求无需人工干预的自动操作。参考文献[8]提出了一种可移动的质心(CoM)的轮式机器人，以方便在崎岖的地形上行走。拟议的系统也考虑通过操纵它的手臂来间接地改变CoM;如何-永远，主要的焦点是在桶中得到反应力作为支撑来举起动力铲履带。 Fig. 1 Basic parts of a power shovel. The coordinate frame convention is X forward, Y left and Z up X (forward) crawler step platform boom joint power shovel bucket bucket joint axis of platform rotation boom arm Z (up) arm joint 问题陈述 如果有一个类似阶梯状的障碍物，动力铲应该机动它的手臂以平稳的轨迹爬上障碍物。此外，它还应该以这样一种方式进行机动，使总能量消耗降到最低。整个过程是自动化的，这样就消除了人类工人的风险。 b stage 2 Fig. 2 Obstacle surmount stages. The power shovel with dotted lines depicts the initial state while the the one with the regular lines depicts the final state for each stage. P1, P2, P3 and αF denote the parameters of the total maneuver. B and E denote bucket and step edge positions respectively B P3 E initial pose of stage 2 Pb P4 step Pb : bottom center position final pose of stage 2 αF P1 a stage 1 E initial pose of stage 1 Pb Pb : bottom center position P2 step B final pose of stage 1 方法 在提出的方法中，障碍超越操作分为两个阶段。在第一阶段，铲斗保持在动力铲的前部，并提供所需的反作用力，使爬虫的正面向上爬升到阶梯状结构;爬虫的尾部保持与地面水平的接触。如图2a所示。第一阶段完成后,平台旋转180°boom-arm-bucket复合移动到后面的电铲启动第二阶段。与第一阶段类似，吊桶提供了所需的反作用力，以提升爬虫的尾部，完成第2阶段的全部surmount操作。如图2b所示。在第一和第二阶段，水桶保持固定的地面位置，使用摩擦力[1]或由斗齿锚定，这是稳定机动的支点;可根据环境选择适合的锚固方法。 讨论 可以看出，CFSQP结果与完全慢批量模拟得到的结果比较好。事实上，CFSQP已经捕获了目标函数(能量)的连续性质，因此能够获得最高效的param- eters，即使在基于较小参数的情况下，也不能被捕获。从CFSQP的能量结果来看，这是明显的，比彻底的慢批量模拟的结果要小。为了使CFSQP运行，必须将修改包含到原始算法中。也就是说，当目标函数的梯度是有限的。 差分逼近,算法倾向于使用附近的点,甚至可以违反给定con -制度化。这可能会导致ODE崩溃，因为输入的定义不明确。为了克服这个问题，在测试不确定的点时注入了大量的成本。 吊杆、臂和桶接头的关节轨迹(图11、12、13)确认关节平稳过渡。然而，每个数字的不连续性需要特别的说明。第一阶段完成后，平台旋转到动力铲的背面开始第二阶段。假设这个简单的操作可以通过恒定的能量来完成，因此为了简单起见，我们省略了分析。因此，由于序列1和序列2-1之间的最终和初始关节的不匹配，可以看到间断。 参数P4被认为是常量。 模拟。P4的唯一要求是，当2-2序列完成后，电铲在提升吊桶后能够保持稳定。在此之前，只要满足这一要求，P4就可以被设定为一个经验值，而不被包含在优化过程中。 open dynamics engine (ODE)[9]包括两个默认求解器，即(1)Dantzig的agm solver。 (2)连续超松弛(SOR)投影高斯- Seidel (PGS) LCP求解器。在这个工作中，Dantzig的agm solver已经被用于实现a。 数值精确解，即使它大约是一个数量级的慢于或PGS LCP求解器。 从图14可以看出，关节突在不同的阶段经历一定的瞬态。在第一阶段的开始阶段，由于两个原因导致转矩瞬变:(1)履带前的接触与地面接触，(2)当桶开始推台阶或地面时产生的内力。类似的情况出现在第二阶段的开始阶段，爬虫的背部(但由于平台旋转而被视为爬虫的前部)开始向上移动并与地面失去联系。另一个重要的观察是重力条件(每一个连杆的质量)在其他术语上占主导地位，比如科里奥利力、向心和惯性项，因为它们的关节速度和加速度相对较小。 作为障碍物的第一步，将一个类似于sim的阶梯状结构作为障碍物。如何——永远不要忘记，使用它的手臂和水桶来改变地形是有好处的。其结果是，它可以将非结构化的地形铺在前面，利用台阶切割法等快速方法将其塑造成阶梯状结构，并采用所提出的方法;将地形完全修改成光滑的边坡需要相当长的时间，这就否定了原来的目的。 未来的工作 提出的方法是解决这一问题的第一步，因此选择了一个简单的阶梯状障碍物。由于问题的对称性，在模拟中可以忽略y坐标运动。此外，臂和桶连接轴相互平行，这使得cor-响应的连接在飞机上移动。这也使我们将三维运动简化为二维空间。然而，在自然灾害之后产生的碎片有非常复杂的形状。作者希望在未来解决各种障碍的问题，这就需要对全三维运动进行分析。克服复杂障碍的另一个方面是稳定性问题。电铲在整个操作过程中应保持其稳定性，在任何情况下都不应倾斜。 在轨迹规划中采用简单的高阶多项式，因为它简单易用，没有遇到任何问题。然而，spline(分段连续多项式)在轨迹规划中得到了popu- larity，作者希望通过将简单的多项式在未来改变为样条函数来观察其改进。 作为下一步，作者希望在未来使用真实的硬件进行扩展，以确认通过模拟获得的结果。 11