基于ADAMS和Vega的地面机动武器仿真系统的研究

结合数值仿真和视景仿真技术，建立了地面机动武器系统的分布式交互仿真平台，该集成仿真系统具备多种仿真功能，能够用于新型武器装备的研制和大规模军事演练。按照该仿真系统结构，实现了某地面移动机器人的仿真系统。其动力学仿真子系统用ADAMS的履带工具箱（ATV）建立了该机器人的动力学模型。并对起步工况、最高直驶速度和转向特性进行了动力学仿真分析，得到该数字系统较为完整的虚拟实验数据，并通过交互接口将仿真数据用于视景驱动。视景仿真子系统采用MultiGen Creator／Vega实现，分析了视景模型的数据组织结构和简化处理，基于Vega编制了视景仿真程序。     

履带式移动机器人轨迹跟踪研究

详细分析了履带式移动机器人的受力特点,提出了一种适宜进行控制器设计的履带移动机器人模型.根据履带式移动机器人动力学模型和运动学模型,设计了机器人的轨迹跟踪控制器.利用Lyapunov稳定判据证明控制器的全局稳定性.在控制器的设计中考虑了履带一地面作用,引入参数对其描述.考虑到机器人动力学约束,引入机器人速度、加速度控制策略以保证机器人运动平滑.仿真实验验证了该方法的有效性和全局收敛.     

基于流函数的多移动机器人Swarming控制模型

利用流函数解决单个移动机器人的避障问题，并提出了基于流函数和单一连接规则的、采用虚拟leader和二叉树结构的多移动机器人swarming控制模型．基于单一连接规则的二叉树结构使得整个机器人群的控制更简单，更灵活；而虚拟leader的引入，使机器人群在避障过程中不会发生分离，并能够很好地解决类似于机器人掉队的问题，提高了系统的稳定性，增强了系统的应变能力．仿真结果验证了该模型的有效性．     

小型地面侦察机器人移动载体技术研究

本文就侦察机器人移动载体作了详细分析，提出了提高机器人地形适应能力的带前摆臂的双节地面移动机器人结构，并对机器人越障过程中机器人整体及前摆臂的受力情况进行了分析，得出驱动力矩及各杆件的受力情况，为双节地面移动机器人技术的研究工作提供了一定的理论依据。最后进行机器人载体运动仿真分析，对爬越楼梯和穿越狭缝的作业环境进行仿真，通过三维动态显示直观地看出机器人载体机构的运动情况及行驶通过性情况。     

基于对象特征模型描述的舱外自由移动机器人地面实验系统预测控制方法

本文基于对象特征建模的思想,在关节角空间和任务空间建立了空间机器人系统的特征模型,提出了一种基于特征模型的舱外自由移动机器人地面实验系统的单步预测控制方法。该方法不需计算机器人动力学方程,不需在线调整控制器参数,具有很强的适应能力,同时设计简单,使用方便,计算量小,适合工程应用。     

多水下机器人视景仿真系统技术研究

该文介绍了多水下机器人群体分佰式智能控制软件的视景仿真系统。以MultiGen Creator建模,利用实时视景开发软件包OpenGL Performer,采用POSIX Thread多线程技术,在Linux环境下开发了分布式多水下机器人三维视景仿真平台。实现了多水下机器人分布式智能控制软件系统的实时视景仿真,保证了整个系统的信息共享与时间同步。同时该文讨论了该视景仿真软件的开发过程以及整个系统的体系结构和信息流程。试验结果表明,该视景系统可逼真演示多水下机器人编队水下航行、作业等过程,并满足系统仿真的实时性要求。     

基于运动描述语言的轮式移动机器人控制

介绍了一种基于运动描述语言的轮式移动机器人控制方法．运动描述语言不仅可以有效地描述机器人系统中离散和连续动力学过程的相互作用，而且可以定量地描述操纵机器人的复杂性．利用该方法对具有非完整约束的轮式移动机器人的位姿镇定问题进行了研究，仿真结果验证了该方法的有效性．     

变结构可抛掷球形机器人的运动分析

针对灾后、战后等复杂地面环境,开发了一种能够以抛掷或发射方式进入工作区域进行作业的变结构机器人.该机器人能够以球形结构通过抛掷或发射的方式越过现有大部分地面移动机器人无法通过的地面障碍.同时,在到达工作区域后,机器人能够变形为具有2个被动自由度的四轮移动机器人以完成移动作业.为了对机器人进行有效的运动控制,针对展开结构建立了考虑前、后车体几何约束及驱动轮无横向滑移约束的运动学模型,分析了机器人在进行曲线运动时产生轨迹误差的原因.仿真得到了机器人做正弦曲线运动时的轨迹误差,并分析了误差的影响因素.通过实验对建立的模型和仿真结果进行了验证,证明机器人具有较好的运动灵活性.     

轮式移动机器人曲线行走控制的实现

从实用的角度出发，对轮式移动机器人沿曲线轨迹行走的控制进行了研究。设计了电机伺服控制系统和定位模块来实现机器人的运动控制系统功能，并基于移动机器人动力学模型设计了稳定有效的曲线行走控制算法。机器人沿抛物线和椭圆轨迹行走的实验结果表明，移动机器人曲线行走控制的硬件结构和软件功能是可行实用的，该户外轮式移动机器人运动控制系统的结构设计和功能设计符合实用要求，具有一定的应用价值。     

基于Vega的双臂空间机器人飞行及捕捉目标的轨迹规划仿真

提出了一种利用Vega来实现双臂空间机器人飞行及捕捉目标的轨迹规划仿真系统．简要介绍了仿真系统的开发环境及其实现方法．该仿真系统在SGI工作站上， 利用Multigen Creator 建模工具和三维视景仿真软件Vega来实现空间机器人本体及被捕捉目标的建模和仿真， 能为机器人的轨迹规划、运动学分析和运动控制的算法设计提供重要信息， 并能对其理论和算法的可行性加以验证．     

Quasi-min-max MPC for visual servoing stabilization of omnidirectional wheeled mobile robots

This paper proposes a new visual servoing quasi-min-max MPC algorithm for stabilization control of an omnidirectional wheeled mobile robot subject to physical and visual constraints. The visual servoing dynamics of the robot are modeled as the state-dependent linear error system with nonlinear control inputs of rotation and deflection velocities of wheels. The state-dependent linear error system is covered as linear parameters-varying models which is used to design the visual servoing quasi-min-max MPC controller. The actual control inputs of the robot are then computed by the solution of an inverse algebraic equation of the MPC actions. The recursive feasibility and stability of the new visual servoing MPC are ensured by some LMIs conditions. The performance and practicability of the visual servoing MPC are verified by some simulation and experiment results.     

Navigating a mobile robot by a traversability field histogram.

This paper presents an autonomous terrain navigation system for a mobile robot. The system employs a two-dimensional laser range finder (LRF) for terrain mapping. A so-called "traversability field histogram" (TFH) method is proposed to guide the robot. The TFH method first transforms a local terrain map surrounding the robot's momentary position into a traversability map by extracting the slope and roughness of a terrain patch through least-squares plane fitting. It then computes a so-called "polar traversability index" (PTI) that represents the overall difficulty of traveling along the corresponding direction. The PTIs are represented in a form of histogram. Based on this histogram, the velocity and steering commands of the robot are determined. The concept of a virtual valley and an exit condition are proposed and used to direct the robot such that it can reach the target with a finite-length path. The algorithm is verified by simulation and experimental results.     

基于立体视觉的移动机器人导航算法

移动机器人立体视觉系统不仅提供三维地形图用于障碍规避和路径规划,其结果还可以用于视觉导航。以移动机器人立体视觉系统为基础,研究了基于前后两个位置上立体图对的视觉测量算法用于移动机器人的连续导航,讨论了影响导航精度的因素和改进方法;研究了基于局部和全局三维地形图的地形匹配算法用于定期校正位置误差,算法实现简便,定位精度取决于地形图精度。实验结果证明了两种方法的有效性,可以兼顾近距离和中远距离导航任务。     

Gyro-based odometry associated with steering characteristics for wheeled mobile robot in rough terrain

Mobile robot used for planetary exploration performs several scientific missions over long distance travel and needs to have a high degree of autonomous mobility system because the communication delay from the Earth impedes its direct teleoperation. Localization of a mobile robot is of particular importance on the autonomous mobility. Classical localization methods such as wheel/visual odometry have been widely investigated and demonstrated, but they possess a well-known trade-off between computational cost and localization accuracy. This paper proposes an accurate gyro-based odometry method for a wheeled mobile robot in rough terrain. The robot in rough terrain is often subject to large wheel slip or vehicle sideslip related with its steering maneuver, and those slips degrade the localization accuracy. The basic approach of the proposed method is to exploit odometry data for the robot distance traveled as well as gyroscope data for the robot heading calculation; however each data-set is weighted in accordance with steering characteristics of a robot in rough terrain. The usefulness of the proposed method is examined through field experiments using a wheeled mobile robot testbed in Martian analog site. The experimental result confirms that the proposed method accurately estimates the robot trajectory.     

视觉地形分类的词袋框架综述

目的 视觉地形分类是室外移动机器人领域的一个研究热点。基于词袋框架的视觉地形分类方法,聚集和整合地形图像的视觉底层特征,建立底层特征统计分布与高层语义之间的联系,已成为目前视觉地形分类的常用方法和标准范式。本文全面综述视觉地形分类中的词袋框架,系统性总结现有研究工作,同时指出未来的研究方向。方法 词袋框架主要包括4个步骤：特征提取、码本聚类、特征编码、池化与正则化。对各步骤中的不同方法加以总结和比较,建立地形分类数据集,评估不同方法对地形识别效果的影响。结果 对词袋框架各步骤的多种方法进行系统性的分类和总结,利用地形数据集进行评估,发现每个步骤对最后生成的中层特征性能都至关重要。特异性特征设计、词袋框架改进和特征融合研究是未来重要的研究方向。结论 词袋框架缩小低层视觉特征与高层语义之间的语义鸿沟,生成中层语义表达,提高视觉地形分类效果。视觉地形分类的词袋框架方法研究具有重要意义。     

基于神经网络的机器人视觉伺服控制

视觉伺服可以应用于机器人初始定位自动导引、自动避障、轨线跟踪和运动目标跟踪等控制系统中。传统的视觉伺服系统在运行时包括工作空间定位和动力学逆运算两个过程,需要实时计算视觉雅可比矩阵和机器人逆雅可比矩阵,计算量大,系统结构复杂。本文分析了基于图像的机器人视觉伺服的基本原理,使用BP神经网络来确定达到指定位姿所需要的关节角度,将视觉信息直接融入伺服过程,在保证伺服精度的情况下大大简化了控制算法。文中针对Puma560工业机器人的模型进行了仿真实验,结果验证了该方法的有效性。     

Hybrid trigonometric compound function neural networks for tracking control of a nonholonomic mobile robot

The purpose of this paper is to propose a hybrid trigonometric compound function neural network (NN) to improve the NN-based tracking control performance of a nonholonomic mobile robot with nonlinear disturbances. In the mobile robot control system, two NN controllers embedded in the closed-loop control system have the simple continuous learning and rapid convergence capability without the dynamics information of the mobile robot to realize the tracking control of the mobile robot. The neuron functions of the hidden layer in the three-layer feedforward network structure consist of the compound cosine function and the compound sine function combining a cosine or a sine function with a unipolar sigmoid function. The main advantages of this NN-based mobile robot control system are better real-time control capability and control accuracy by use of the proposed NN controllers for a nonholonomic mobile robot with nonlinear disturbances. Through simulation experiments applied to the nonholonomic mobile robot with the nonlinear disturbances of dynamics uncertainty and external disturbances, the simulation results show that the proposed NN control system of a nonholonomic mobile robot has better real-time control capability and control accuracy than the compound cosine function NN control system of a nonholonomic mobile robot and then verify the effectiveness of the proposed hybrid trigonometric compound function NN controller for improving the tracking control performance of a nonholonomic mobile robot with nonlinear disturbances.     

A systematic method of dynamics for flexible robot manipulators

In this article, a systematic method to derive dynamic equations of motion for flexible robot manipulators is developed by using the Lagrangian assumed modes method. The proposed method can be applied to dynamic simulation and control system design for flexible robot manipulators. In the proposed method, the link deflection is described by a truncated modal expansion. The operations of only 3x3 matrices and/or 3 × 1 vectors exist in the method. All the dynamics computations are performed in the link coordinate systems, where the kinematics informations are computed with the forward recursion from the base to the hand tip and the dynamics informations are computed with the return recursion. As generally compared with other existing methods, the method proposed in this article is, computationally, more simple, systematic, and efficient. A computational simulation for a single-link flexible robot manipulator is presented to verify the proposed method. © 1992 John Wiley & Sons, Inc.     

Path planning for a tracked robot traversing uneven terrains based on tip-over stability

In the real-world environment, the path planning method of tracked robot is widely studied when driving on uneven terrain. How to solve the problem that the traditional path planning algorithm cannot adapt to uneven terrain because of the constraints of obstacle avoidance and path length is a challenge for tracked robots. In this paper, a stability-based path planning framework for tracked robot is proposed to reduce the risk of rollover when the tracked robot passes through uneven terrain. First, a virtual plane method is proposed to estimate the attitude of tracked robot. Second, on this basis, a dynamic high-stability path evaluation algorithm for tracked robot based on force angle stability margin (FASM) is proposed, which transforms the stability-based path planning problem into a hypergraph problem. Moreover, considering that the optimization problem is strongly nonlinear and nonconvex, a hybrid algorithm of covariance matrix adaptive evolution strategy (CMAES) and Levenberg–Marquardt (LM) is designed under the framework of generalized graph optimization (G2O) to improve the solution efficiency. Finally, simulation and experiments show that the stability-based path planning framework can effectively plan the high-quality path, and the maximum stability of the tracked robot is 0.9156 when the robot crosses uneven terrain using optimal path 2.