关键词： 轮式机器人   动力学建模   高速漂移   姿态跟踪  

摘要： 能够高速、高机动地行驶是轮式移动机器人研制的主要目标之一。本文针对四轮独立驱动的高速轮式滑动转向移动机器人，围绕机器人高速行驶状态下的动力学模型及漂移控制方法进行研究，主要工作包括以下三个方面:\n 1)针对机器人在高速机动状态尤其是漂移状态下轮胎存在明显滑动并且失去运动学约束的问题，本文建立了适用于正常行驶状态（轮胎无明显滑动）和漂移状态（有纵向或横向的明显滑动，或同时存在）的统一动力学模型。本文首先引述了统一轮胎模型，阐述了如何计算漂移工况下地面对轮胎摩擦力;然后，以统一轮胎模型为基础对移动机器人进行了动力学建模，得到了其动力学方程，并对方程特点进行了分析。\n 2)针对机器人具有强耦合、冗余驱动、非线性等特点，本文以动力学模型为基础，设计了一种面向姿态角及姿态角速度跟踪的漂移运动控制器。首先，为了将动力学模型应用到漂移过程的姿态跟踪控制任务中，对姿态动力学方程进行了近似化处理;然后，借鉴线性滤波降阶方法设计了一种基于动力学的漂移运动控制器;最后，以NK-Rover2高速轮式移动机器人为基础，通过仿真与实验两方面对漂移运动控制器的性能进行了实验验证。实验结果表明，漂移运动控制器基本有效，可以完成基本的姿态漂移任务。\n 3)针对视觉导航、GPS等定位方法实时性差，不能满足高速漂移控制任务的问题，本文设计实现了高实时性的位置速度测量单元，为移动机器人定位提供了一种新的方法。

关键词： 空间绳系机器人   有限单元法   Hamilton原理   Newton—Raphson迭代  

摘要： 针对经典"珠子"模型在计算精度和求解速度方面的不足,提出了一种基于有限单元法的高精度建模与快速求解方法。首先在考虑系绳非线性应力-应变关系的基础上,利用Hamilton原理和C-W方程推导了系统在轨道坐标系下的动力学模型,然后使用三阶的一维单元对系绳进行了离散化处理,并给出了一种利用纽马克-β法进行预估,由Newton-Raphson法进行迭代校正的高效时域求解算法,从而实现了对于系统状态的高精度快速求解。仿真结果表明:与经典的"珠子"模型相比,在分段长度相近的情况下,本文的方法不仅求解精度更高,而且计算速度能够提高至少10倍,另外还能够避免仿真过程中张力出现虚假振荡。

关键词： 动力学滑模控制   温室喷药   移动机器人   转弯控制   四轮驱动  

摘要： 随着科技和社会经济的发展，农业自动化程度越来越高，温室已成为现代农业中的重要组成部分。由于温室环境密闭，使得在温室中喷洒农药易残留不易挥发，工作人员极易发生中毒的风险，用机器人代替人类进行温室喷药不但能有效减少人员伤害，而且能实现精准施药，提高农药的利用率。为实现温室喷药移动机器人的自主作业，有必要研究温室喷药移动机器人的运动控制问题。本文着重开展四轮独立驱动温室喷药移动机器人的转弯控制研究。\n 在温室狭窄的环境中，由于地面潮湿，且凹凸不平，对于处于一定速度下的四轮独立驱动移动机器人在转向行驶时极易出现动力学不稳定的状态，造成四轮独立转向移动机器人的受控性降低，出现转向不足或转向过度，从而导致机器人侧滑失控，以致毁坏温室植物和机器人本身，造成严重损失。为此，本文针对四轮独立驱动移动机器人在温室环境下的转弯控制问题，提出一种基于滑模控制理论的动力学滑模控制方法。本文主要研究内容如下:\n 1.针对温室喷药移动机器人转弯控制问题，首先建立了以质心侧偏角和横摆角速度为状态变量的四轮独立转向动力学模型，运用直接横摆力矩控制方法，基于滑模变结构控制理论，设计以质心侧偏角和横摆角速度为控制系统状态变量的指数趋近律动力学滑模控制策略，以使移动机器人质心侧偏角控制在稳定范围内，且其横摆角速度能够很好地跟踪移动机器人期望运动轨迹。通过基于Matlab/Simulink进行转向行驶仿真试验结果表明，与前馈反馈控制方法相比，基于所建立动力学模型所设计滑模控制策略有效改善了移动机器人转弯控制的稳定性。\n 2.设计了基于超声波测距的紧急避障系统，根据不同的温室作业环境可以设置不同的安全距离，当超声波测到离障碍物的距离小于安全距离时可让机器人紧急停止以防止机器人损坏农作物，造成损失。试验表明，所设计紧急避障系统，能较好地满足温室喷药移动机器人对避障的稳定性、快速性要求。\n 3.以实验室改装的四轮独立驱动温室移动机器人系统为试验平台，在Visual Studio6.0开发环境中基于C++语言完成了温室移动机器人运动控制系统软件设计，着重介绍了其运动控制模块与避障模块。最终将本文设计的滑模运动控制算法实际应用于温室环境进行了转弯控制试验，试验结果验证了本文提出的运动控制算法对提高温室移动机器人转弯运动稳定性的有效性。另外，在实验室完成了对于基于超声波的紧急避障试验，试验结果表明本课题的超声波避障系统能够实现安全避障控制。

关键词： ROBOTICS in medicine   SURGICAL robots   GYNECOLOGIC surgery  

摘要： A letter to the editor is presented in response to an article on the use of robotics in benign gynecologic surgery.

关键词： Robotics  

摘要： The proposed Icebreaker mission is a return to the Mars polar latitudes first visited by the Phoenix mission in 2007-2008. Exploring and interrogating the shallow subsurface of Mars from the surface will require some form of excavation and penetration, with drilling being the most mature approach. A series of 0.5-5m automated rotary and rotary-percussive drills developed over the past decade by NASA Ames and Honeybee Robotics provide the capability to fly on a Mars surface mission within the next decade. Surface robotics have been integrated for sample transfer to deck instruments, and the Icebreaker sample acquisition system has been tested successfully in Mars chambers and analog field sites to depths between 1 and 3m, most recently in the Antarctic Dry Valleys in January of 2013. This paper provides a hardware and software systems overview of the Icebreaker sample acquisition system, and discusses test results of this robotic system in relevant environments. Test results from recent Arctic and Antarctic field campaigns demonstrate a hands-off dust to data capability.

关键词： Motion planning   computational complexity   configuration space   robot manipulators  

摘要： This paper formulates a new minimum constraint removal (MCR) motion planning problem in which the objective is to remove the fewest geometric constraints necessary to connect a start and goal state with a free path. It describes a probabilistic roadmap motion planner for MCR in continuous configuration spaces that operates by constructing increasingly refined roadmaps, and efficiently solves discrete MCR problems on these networks. A number of new theoretical results are given for discrete MCR, including a proof that it is NP-hard by reduction from SET-COVER. Two search algorithms are described that perform well in practice. The motion planner is proven to produce the optimal MCR with probability approaching 1 as more time is spent, and its convergence rate is improved with various efficient sampling strategies. It is demonstrated on three example applications: generating human-interpretable excuses for failure, motion planning under uncertainty, and rearranging movable obstacles.

关键词： Neuro-interface   Neural network   Non-holonomic mobile robot   On-line feedback-error learning   Agricultural robot  

摘要： The present study represents agricultural applications of non-holonomic mobile robots. Agricultural robots are significantly affected by various disturbances such as a loading capacity and modeling errors of robots. Abundant studies of mobile robots using online learning have investigated real-time elimination of control errors that are associated to inaccurate modeling of robots and controls of disturbance effects by online learning using neural network. However, a certain problem from errors of online learning may occur in case of the robot that is located on out of tracking path. The above problem may be resulted in the difference by control errors occurring between desired values and current values. Therefore, stepwise optimization of robot control with desired values should be necessary. Online learning for agricultural mobile robots is possibly performed with accurate calculation of control errors using the stepwise optimization of desired values as a standard. In summary, the present study demonstrates a reference robot is used to calculate accurate control errors for non-holomic mobile robot that is driven by pulse. The control error of the non-holonomic mobile robot through online feedback-error learning is almost 1.3% in agricultural application.

关键词： computational reflection   generative programming   robotics framework   dynamic languages   Python   Java Scripting API  

摘要： SUMMARY The development of service robots has gained more attention over the last years. Advanced robots have to cope with many different situations emerging at runtime, while executing complex tasks. They should be programmed as dynamically adaptive systems, capable of adapting themselves to the execution environment, including the computing, user, and physical environment. Recently, dynamic languages are becoming widely used because of the high runtime adaptability they offer. Therefore, we have analyzed the suitability of these languages to implement robotic systems with high runtime adaptability requirements, using Python as case study because of its maturity. To evaluate their suitability, we have implemented a reflective robotics framework that can be programmed in both Java and any dynamic language supported by the standard Java Scripting API. An example scenario has been developed using Python to show how its distinguishing meta-programming features have facilitated the development of runtime-adaptable robotics services. Copyright © 2012 John Wiley & Sons, Ltd. [PUBLICATION ABSTRACT]

关键词： ROBOTICS in medicine   GYNECOLOGY  

摘要： An introduction is presented in which the editor discusses robotics in gynecology.

关键词： Robot dancing   Robot learning   Robot adaptation   Robot interaction with humans  

摘要： In this paper, we investigated an approach for robots to learn to adapt dance actions to human's preferences through interaction and feedback. Human's preferences were extracted by analysing the common action patterns with positive or negative feedback from the human during robot dancing. By using a buffering technique to store the dance actions before a feedback, each individual's preferences can be extracted even when a reward is received late. The extracted preferred dance actions from different people were then combined to generate improved dance sequences, i.e. performing more of what was preferred and less of that was not preferred. Together with Softmax action-selection method, the Sarsa reinforcement learning algorithm was used as the underlining learning algorithm and to effectively control the trade-off between exploitation of the learnt dance skills and exploration of new dance actions. The results showed that the robot learnt, using interactive reinforcement learning, the preferences of human partners, and the dance improved with the extracted preferences from more human partners.