一种外骨骼式康复机器人训练效果仿真

针对外骨骼式下肢康复机器人训练有效性的问题,开展了基于人体生物力学软件Any Body的康复训练仿真实验研究.通过人体动作捕捉实验,获取一成年男子在正常步行时的运动学信息,利用Any Body建立人体步行模型,并以下肢肌肉受力情况为依据确定下肢主要肌肉群.建立人-机系统模型,借助Hill方程,以人体下肢肌肉收缩速率作为判断标准,通过模拟实现矢状面内运动的外骨骼式下肢康复机器人的康复运动,获取下肢主要肌肉的收缩速率变化情况,并将其与正常步行时的肌肉收缩速率进行比较与分析.结果表明,两种情况下大腿肌肉群的收缩速率变化情况基本一致,小腿与髋部肌肉群差异较明显.改进外骨骼结构,使其能够同时实现在冠状面内的运动,比较在两种结构下的下肢主要肌肉收缩速率变化情况,结果表明髋部肌肉产生了较为明显的波动.因此,能实现矢状面内运动的外骨骼式下肢康复机器人能够有效训练大腿肌肉群,但对小腿与髋部肌肉的训练效果不明显,加入冠状面运动后,能提高对髋部肌肉的训练效果.

基于人机闭环仿真的无人直升机操作响应类型研究

针对无人直升机低空飞行操纵控制过程中,控制难度大,操纵负荷大等问题,该文综合无人直升机操纵模型、低空风扰模型等形成人-机-环境闭环模型。基于无人直升机飞行控制律研究与设计采用指令姿态响应类型、指令速度响应类型和指令位置响应类型3类操作响应类型,并通过增益、插值表的应用,实现各响应类型的综合。在此基础上,完成人工自动着陆仿真,结果表明3类操作响应类型综合后能够有效提高控制精度,减轻操作手负担。

结构驾驶员模型与 McRuer 模型的仿真研究

根据驾驶员完成俯仰跟踪的人－机半物理实时仿真实验，分别对结构驾驶员模型和ＭｃＲｕｅｒ模型进行了参数辨识，用两种模型和某电传操纵飞机纵向短周期等效系统模型构成人－机数值仿真系统，将模型仿真结果和实时仿真结果进行比较和分析，以便了解两种模型的特性，为深入研究闭环飞行品质提供参考依据。

虚拟人行为仿真智能化探讨

在虚拟人-机-环境系统研究中,为了评估人与环境的匹配性和协调性,不仅需要虚拟人具有某些静态属性和一般意义上的肢体运动属性,还需要虚拟人逼真地模拟人类执行各种任务的过程。通常,进行序列运动后目的物的操作由手或脚完成。本文在分析虚拟人运动结构及控制的基础上,研究了虚拟人行走、坐立、弯腰、转体等行为动作的实现方法,提出了虚拟人操作行为连续、复合运动仿真的逻辑步骤,并给出了相应举例。

多维比例微分非线性飞行员模型及仿真应用

为更好地仿真研究飞行员事故避免能力和人-机闭环系统的驾驶员诱发震荡(PIO, Pilot Induced Oscillation)特性,提出将飞行员模型按"生理-心理-生理"统一分解为"输入(信号)、处理(决策)、输出(动作)"三个模块,并提出一种新型多维比例微分型非线性飞行员模型(MPDNLPM,Multi-Dimension Proportion-Differential Nonlinear Pilot Model)。结合某机着舰backside跟踪控制状态下动力学模型进行了仿真研究。结果表明:人-机闭环系统控制效果略优于理想P控制;成熟飞行员仍可出现PIO;恰当的预估、及时的响应和合理的操纵增益控制是防止PIO和事故的三项关键能力;提出的模块化分解方法合理、有效;MPDNLPM可揭示人-机系统的内在规律。

Design of a novel modular self-reconfigurable robot capable of self-turning

To solve the problem of inaccurate angle adjustment in the self-assembly process, a new homogenous hybrid modular self-reconfigurable robot-Xmobot is designed. Each module has four rotary joints and a self-turning mechanism. With the proposed self-turning mechanism, the angle adjusting accuracy of the module is increased to 2°, and the relative position adjusting efficiency of the module in the self-assembly process is also improved. The measured maximum moving distance of the proposed module in a gait cycle is 11.0 cm. Aiming at the multiple degree of freedom （MDOF） feature of the proposed module, a motion controller based on the central pattern generator （CPG） is proposed. The control of five joints of the module only requires two CPG oscillators. The CPG-based motion controller has three basic output modes, i. e. the oscillation, the rotation, and the fixed modes. The serpentine and the wheeled movements of the H-shaped robot are simulated, respectively. The results show that the average velocities of the two movements are 15. 2 and 20. 1 m/min, respectively. The proposed CPG-based motion controller is evaluated to be effective.

Motion simulation and experiment of a novel modular self-reconfigurable robot

Based on the character of the modular self-reconfigurable （MSR） robot, a novel homogeneous and lattice MSR robot, M-Cubes, was designed. Each module unit of the robot has 12 freedoms and is composed of six rotary joints and one cubic link. An attached/detached mechanism was designed on the rotary joints. A novel space transmitting system was placed on the inner portion of the cubic link. A motor separately transmitted torque to the six joints which were distributed equally on six surfaces of the cubic link. The example of a basic motion for the module was demonstrated. The result shows that the robot is concise and compact in structure, highly efficient in transmission, credible in connecting, and simple in controlling. At the same time, a simulator is developed to graphically design the system configuration, the reconfiguration process and the motion of cluster modules. The character of local action for the cellular automata （CA） is utilized. Each module is simplified as a cell. The transition rules of the CA are developed to combine with the genetic algorithm （GA） and applied to each module to accomplish distributed control. Simulation proves that the method is effective and feasible.

A sensor-based motion planner: Situated-Bug

Propose a new sensor-based motion planning approach of Situated-Bug, which is composed of goal-oriented behavior, boundary following behavior and goal-oriented obstacle avoidance behavior, which are based on fuzzy control. The situated-Bug selects its behaviors according to robot orientation, instead of positions and hit points like other Bug algorithms, and its convergence proves robust to sensor noise, and it can guide the robots running for long rang traverse. At the same time, the design of the Situated-Bug is presented. Simulation results show that the approach is effective and practical.

Semi-physical simulation of AUV pipeline tracking

Before the task of autonomous underwater vehicle(AUV) was implemented actually,its semi-physical simulation system of pipeline tracking had been designed.This semi-physical simulation system was used to test the software logic,hardware architecture,data interface and reliability of the control system.To implement this system,the whole system plan,including interface computer and the methods of pipeline tracking,was described.Compared to numerical simulation,the semi-physical simulation was used to test the real software and hardware more veritably.In the semi-physical simulation system,tracking experiments of both straight lines and polygonal lines were carried out,considering the influence of ocean current and the situation of buried pipeline.The experimental results indicate that the AUV can do pipeline tracking task,when angles of pipeline are 15°,30°,45° and 60°.In the ocean current of 2 knots,AUV could track buried pipeline.

驾驶员模型建模精度分析方法研究

针对频域内驾驶员描述函数的辨识方法和最小二乘的驾驶员模型参数的估计方法，按照精度公式的规范条件建立了驾驶员模型建模精度评价公式。并对驾驶员完成俯仰跟踪任务时的仿真结果和驾驶员模型辨识结果进行了精度检验计算，同时还探讨了提高建模精度的有关技术问题（包括非参数模型与参数模型）。

A robot simulation system with virtual force display and feedback based on master manipulator

This paper describes a virtual environment, which can present dynamic force transformation during the control of objects. A 5-DOF haptic interface with the capability to generate kinesthetic effect is combined. In this system, the operator manipulates an object in a virtual environment by using the 5-DOF master arm. When contacting with the virtual object, the contact force can be calculated and shown in the graphic interface. The contact response and deformation of the virtual object, which are usually called haptic rendering, also can be performed. The study supplies an approach to improve the operator’s immersion and can be used in many tele-robot control fields.

ADAPTIVE NEURAL NETWORK ATTITUDE CONTROL FOR UNMANNED HELICOPTER

Adaptive flight control technology, feedback linearization, model inversion theory are reviewed and the error dynamic characteristics are analyzed, and an adaptive on-line neural network attitude control system is presented. The model inversion is under the hover condition. And the adaptive control law based on the neural network is designed to guarantee the boundedness of tracking error and control signals. Simulation results demonstrate that the nonlinear neural network augmented model inversion can self-adapt to the uncertainty and modeling errors of unmanned helicopters. Results are compared while the parameters of PD controller and robustness items are changed.

Mobile robot path planning based on adaptive bacterial foraging algorithm

The utilization of biomimicry of bacterial foraging strategy was considered to develop an adaptive control strategy for mobile robot, and a bacterial foraging approach was proposed for robot path planning. In the proposed model, robot that mimics the behavior of bacteria is able to determine an optimal collision-free path between a start and a target point in the environment surrounded by obstacles. In the simulation, two test scenarios of static environment with different number obstacles were adopted to evaluate the performance of the proposed method. Simulation results show that the robot which reflects the bacterial foraging behavior can adapt to complex environments in the planned trajectories with both satisfactory accuracy and stability.

Task Assignment for Forest Fire Suppression by Multiple UAVs

This paper presents a scenario of forest fire suppression using UAVs （Unmanned Aerial Vehicles） and addresses task assignment algorithm to coordinate UAVs. Forest fires are a major problem in many nations and fast extinguishing forest fires brings a lot of ecological advantages so proper use of firefighting resources is very critical. In this sense, multi UAVs forest fire suppression system can be effective way to prevent fire outbreaks. In multi agent system, an appropriate task assignment according to the SA （Situational Awareness） is the most essential to conduct mission. We should consider real time re-planning or re-scheduling of multi UAVs team because environmental situations such as wind are changeable and that changes affect the forest fire spreading. Furthermore, we have to think about convergence to a consistent SA because it may take too much time. CBBA （Consensus-Based Bundle Algorithm） is robust decentralized task assignment tool so it can be implemented in real time re-planning application. A simulation model which is the main topic in this paper shows that multi UAVs can be properly operated to suppress forest fires even if there are unpredictable random factors and partial disconnection. The simulation model includes concrete operating scenarios and recursive task re-assign algorithm until fires in the whole area are suppressed.

Navigation of Robot Using VFH＋ Algorithm

This paper describes a reactive navigation proposed for a differentially driven robot. The aim of the reactive navigation is to prescribe behavior to the robot based on actual sensor values that is collision-free. Analysis of reactive navigation methods shows that there is no reliable reactive collision-free method. However, method VFH＋ is suboptimal reactive navigation method for static environment. Original method was proposed for ultrasonic rangefinders. Nowadays, much more sophisticated sensors are available. That is why our modification is proposed for a laser rangefinder attached to indoor mobile robot. Results are presented as simulation in Matlab and also as experiments with real robot. Based on these experiments, it can be claimed that VFH＋ is very effective reactive navigation method for various sensors and environments and it can be modified for different requirements on robot behavior.

Three-layer intelligence of planetary exploration wheeled mobile robots:Robint,virtint,and humint

The great success of the Sojourner rover in the Mars Pathfinder mission set off a global upsurge of planetary exploration with autonomous wheeled mobile robots(WMRs),or rovers.Planetary WMRs are among the most intelligent space systems that combine robotic intelligence(robint),virtual intelligence(virtint),and human intelligence(humint) synergetically.This article extends the architecture of the three-layer intelligence stemming from successful Mars rovers and related technologies in order to support the R&D of future tele-operated robotic systems.Double-layer human-machine interfaces are suggested to support the integration of humint from scientists and engineers through supervisory(Mars rovers) or three-dimensional(3D) predictive direct tele-operation(lunar rovers).The concept of multilevel autonomy to realize robint,in particular,the Coupled-Layer Architecture for Robotic Autonomy developed for Mars rovers,is introduced.The challenging issues of intelligent perception(proprioception and exteroception),navigation,and motion control of rovers are discussed,where the terrains' mechanical properties and wheel-terrain interaction mechanics are considered to be key.Double-level virtual simulation architecture to realize virtint is proposed.Key technologies of virtint are summarized:virtual planetary terrain modeling,virtual intelligent rover,and wheel-terrain interaction mechanics.This generalized three-layer intelligence framework is also applicable to other systems that require human intervention,such as space robotic arms,robonauts,unmanned deep-sea vehicles,and rescue robots,particularly when there is considerable time delay.

An area-based position and attitude estimation for unmanned aerial vehicle navigation

The paper aims to challenge non-GPS navigation problems by using visual sensors and geo-referenced images. An area-based method is proposed to estimate full navigation parameters(FNPs), including attitude, altitude and horizontal position, for unmanned aerial vehicle(UAV) navigation. Our method is composed of three main modules: geometric transfer function, local normalized sobel energy image(LNSEI) based objective function and simplex-simulated annealing(SSA) based optimization algorithm. The adoption of relatively rich scene information and LNSEI, makes it possible to yield a solution robustly even in the presence of very noisy cases, such as multi-modal and/or multi-temporal images that differ in the type of visual sensor, season, illumination, weather, and so on, and also to handle the sparsely textured regions where features are barely detected or matched. Simulation experiments using many synthetic images clearly support noise resistance and estimation accuracy, and experimental results using 2367 real images show the maximum estimation error of 5.16(meter) for horizontal position, 9.72(meter) for altitude and 0.82(degree) for attitude.