Collision avoidance for a mobile robot based on radial basis function hybrid force control technique

Collision avoidance is always difficult in the planning path for a mobile robot. In this paper, the virtual force field between a mobile robot and an obstacle is formed and regulated to maintain a desired distance by hybrid force control algorithm. Since uncertainties from robot dynamics and obstacle degrade the performance of a collision avoidance task, intelligent control is used to compensate for the uncertainties. A radial basis function （RBF） neural network is used to regulate the force field of an accurate distance between a robot and an obstacle in this paper and then simulation studies are conducted to confirm that the proposed algorithm is effective.

Direct and Inverse Kinematic Analysis of a Leg-wheeled Passive Wheel Mobile Robot - Ice-skater Robot

A new passive wheel type of leg-wheeled mobile robot based on rolling principle was introduced. To enhance the stability and maintain vertical to the ground of wheels, four passive wheels were installed at the end of four legs respectively and parallel mechanisms were used as legs. And an inertia coordinate system and a robot coordinate system were established, the related kinematic equation of the robot was gotten according to some assumptions after the configuration or the posture of wheels and legs was analyzed. At the same time, the turning conditions of the robot were also obtained. Based on the motion principle, the VSS-based logic control system was designed and the skating straight experiments and the turning experiments were conducted. And some conclusions were drawn.

PRINCIPLE, CONSTRUCTION AND KINEMATIC ANALYSIS FOR THE OMNIDIRECTIONAL MOBILE ROBOT——ICE-SKATER ROBOT

Three main basic types of locomotion for a mobile robot were introduced and the advantages and disadvantages of a legged mobile robot, a wheeled mobile robot and an articulated mobile robot were also discussed. A new type of leg wheeled mobile robot was introduced which combines the adaptability of legged robot with the stability of wheeled robot. On the basis of the structure of the wheels, the paper described the principle of the ice skater robot developed from Roller walker and ALDURO and its construction. The paper also established an inertia coordinate system and a wheel coordinate system, and analyzed the configuration or the posture and the related kinematic constraints of the robot according to some assumptions. Based on the motion principle, a logic based coordinated control system and corresponded flowchart were designed. At last, taking the ice skater robot as an example the paper expounded its application and the actual experiment proved its feasibility.

Robotic Walker for Slope Mobility Assistance with Active-Passive Hybrid Actuator

Walking assistance can be realized by active and passive robotic walkers when their users walk on even roads.However,fast signal processing and real-time control are necessary for active robotic walkers when the users walk on slopes,while assistive forces cannot be provided by passive robotic walkers when the users walk uphill.A robotic walker with an active-passive hybrid actuator(APHA)was developed in this study.The APHA,which consists of a rotary magnetorheological(MR)brake and a DC motor,can provide mobility assistance to users walking both uphill and downhill via the cooperative operation of the MR brake and DC motor.The rotary MR brake was designed with a T-shaped configuration,and the system was optimized to minimize the brake volume.Prototypes of the APHA and robotic walker were constructed.A control algorithm for the robotic walker was developed based on the characteristics of the APHA and the structure of the robotic walker.The mechanical properties of the APHA were characterized,and experiments were conducted to evaluate the mobility assistance supplied by the robotic walker on different roads.The results show that the APHA can meet the requirements of the robotic walker,and suitable assistive forces can be provided by the robotic walker,which has a simple mechanical structure and control method.

基于改进Hybrid A^(*)算法的阿克曼移动机器人路径规划

针对移动机器人路径规划的效率和所规划路径的安全性问题,基于阿克曼六轮转向模型,提出了一种基于改进Hybrid A^(*)算法的路径规划方法。通过改进Hybrid A^(*)算法中的启发式函数,引入距离惩罚函数,减少了节点搜索数量;通过构建安全走廊,引导移动机器人尽可能远离障碍物;在代价函数中加入了节点向前、换向和向后扩展的惩罚项,确保所规划路径的可执行性与安全性。通过仿真表明,基于改进Hybrid A^(*)算法的路径规划方法适用于阿克曼六轮移动机器人,提高了路径规划的效率,规划的路径更具安全保障。

Motion design of a hybrid wheeled/legged robot for lunar exploration

The robot consists of a quadruped mechanism and two active dual-wheel casters possesses the advantages of wheeled and legged mechanism, and can quickly move on the relatively plane ground with the wheeled mechanism, and can walk on the extremely uneven terrain with the legged mechanism. The effectiveness of the motion design of the hybrid robot is iHustrated by simulation results.

Base placement optimization of a mobile hybrid machining robot by stiffness analysis considering reachability and nonsingularity constraints

The mobile hybrid machining robot has a very bright application prospect in the field of high-efficiency and high-precision machining of large aerospace structures.However,an inappropriate base placement may make the robot encounter a singular configuration,or even fail to complete the entire machining task due to unreachability.In addition to considering the two constraints of reachability and non-singularity,this paper also optimizes the robot base placement with stiffness as the goal to improve the machining quality.First of all,starting from the structure of the robot,the reachability and nonsingularity constraints are transformed into a simple geometric constraint imposed on the base placement:feasible base placement area.Then,genetic algorithm is used to search for the base placement with near optimal stiffness(near optimal base placement for short)in the feasible base placement area.Finally,multiple controlled experiments were carried out by taking the milling of a protuberance on the spacecraft cabin as an example.It is found that the calculated optimal base placement meets all the constraints and that the machining quality was indeed improved.In addition,compared with simple genetic algorithm,it is proved that the feasible base placement area method can shorten the running time of the whole program.

改进Hybrid A^(*)的拖挂式移动机器人路径规划算法

为了提高传统Hybrid A^(*)算法的路径规划效率和安全系数,提出一种改进的Hybrid A^(*)路径规划算法,并将此算法应用在拖挂式移动机器人系统上。首先,对启发函数进行改进,以减少路径规划过程中的计算量,从而提高规划效率;其次,设计障碍惩罚函数,进而实现提前避开行进路径上的障碍物,避免在U型障碍中陷入局部最优解;最后,考虑到拖挂式机器人模型结构的特殊性,无法将其视为质点,为此采用碰撞检测算法来提高规划路径的合理性和准确性。仿真试验验证,提出的改进Hybrid A^(*)路径规划算法可适用于拖挂式机器人系统,且具有规划效率和安全性能高、路径平滑等特点,为其在实际应用中的路径规划提供理论依据。

面向复合地图的移动机器人分层路径规划

针对传统路径规划方法在部分未知复杂大场景环境下搜索空间大、效率低、避障成功率不高等问题,提出一种基于拓扑-栅格-度量复合地图的移动机器人分层路径规划方法。首先将机器人作业环境描述为栅格地图并划分为多个栅格化的子区域,以子区域为关键节点进行位置关系抽象从而获得拓扑架构,并对局部栅格区域进行精细化描述,构建拓扑-栅格-度量的复合地图。其次,在不同地图层级上分区域搜索机器人路径,在拓扑地图上采用Floyd算法规划子区域之间的区间路径,面向栅格地图提出搜索子区域内部路径的改进A^(*)算法,通过引入扩展点筛选策略、双向搜索机制、路径冗余点剔除技术提高路径规划的效率与质量,并拼接各段区间路径和内部路径生成全局优化初始路径。最后,针对部分未知场景中的动态障碍物,在度量地图上提出基于深度强化学习架构的动态避障路径规划方法,利用价值分类经验回放机制提高样本的利用率和模型训练的效率。实验结果表明,所提方法有较高的搜索效率和避障成功率,生成的路径兼具安全性和平滑性。

面向纺织生产环境的移动机器人定位方法

纺织行业的智能化、绿色化是“双碳”战略中必须进行升级的内容,移动机器人的大量应用将是未来趋势,但是各类纺机中的电动机、传动机构等在生产过程中产生的电磁环境不利于机器人定位。为解决上述问题,提出一种多传感器混合滤波方法,通过结合基于自适应蒙特卡洛定位(adaptive Mentcarto localization, AMCL)方法和无迹卡尔曼滤波(unscented Kalman filter, UKF)融合定位来保证定位的精度;将AMCL与轮式里程计、惯性导航、激光里程计结合使用,根据惯性导航数据对各传感器数据进行预处理减少误差的引入;并通过UKF滤波器进行局部姿态估计。最后,基于机器人操作系统(ROS)框架,利用Gazebo仿真软件构建无、有电磁干扰的纺织车间环境进行试验。结果表明:在无电磁干扰的仿真环境中,AMCL-UKF混合滤波算法定位精度相较于扩展卡尔曼(extended Kalman filter, EKF)融合定位算法、UKF融合定位算法,精度分别提升26.9%、26.0%。在有电磁干扰环境中引入误差减小36.7%。提出的定位方法能够有效提高移动机器人室内定位的精度,对于纺织生产电磁环境下具有较好的稳定性。

改进A*算法的移动机器人全局路径规划研究

针对传统A*算法在全局路径规划时存在实时性差与安全性不足的缺陷,提出融合JPS与安全权重方阵的改进A*算法对移动机器人的路径进行优化。将传统A*算法融合JPS选取跳点思想,减少路径规划过程中选取扩展节点需要计算的节点数量,提升算法实时性;在寻路过程中增加安全权重方阵思想,通过计算其安全系数与障碍物因子来更新函数代价值,使机器人与障碍物保持相应距离,提升算法安全性。最后利用不同大小的栅格地图进行仿真,结果证明,提出的融合JPS与安全权重方阵的改进A*算法在保持寻路搜索效率更高的前提下,也能保证路径轨迹更安全。

基于改进火烈鸟搜索算法的移动机器人路径规划

为改善火烈鸟搜索算法(FSA)在路径规划中易陷入局部误区的问题,提出改进FSA(IFSA)用于移动机器人路径规划。该算法引入自适应Sigmoid非线性因子实现种群动态调整,平衡了算法的全局搜索与局部搜索;同时,嵌入自适应混合精细分级的觅食位置更新方式,增强算法局部寻优能力;进一步提出随机镜面反射学习(RSRL)机制并应用于算法种群逐维学习,提高算法的寻优效率与精度。实验结果表明:IFSA能够快速获取最短路径,寻优能力优于其他算法,具有较强的稳定性和鲁棒性。

基于运动约束的移动机器人路径规划

针对A*算法路径规划中存在的转折冗余、安全性低、不符合移动机器人非完整约束模型等问题,提出一种基于运动约束的路径规划算法。首先,通过挪移处理使A*算法规划的路径点适度远离障碍物。然后,剔除无障碍路径点间节点,获取路径必经转折点。最后考虑机器人运动约束,以转折点位姿为局部目标,引导混合A*二次规划路径。实验结果表明,改进算法比传统A*算法提高了65%的安全距离,无冗余转向,路径具有位姿连续性,可以保证机器人的平稳、高效、安全的移动。

基于绳驱并联机器人系统刚度的力/位混合控制

对8绳6自由度绳驱并联机器人进行支撑刚度分析,基于刚度模型进行了力/位混合控制研究。首先,对绳驱并联机器人进行系统描述;接着,根据矢量封闭原理进行运动学分析,并对动平台进行受力分析,推导出静力平衡方程;然后,在操作空间通过刚度矩阵建立负载变化与位姿变化之间的关系,推导出支撑刚度的解析表达式,进而分析了影响支撑刚度的因素。另外,考虑系统刚度、动平台位姿精度和力控制稳定性等因素,综合出力/位混合控制器。仿真结果表明,在系统刚度基础上提出的力/位混合控制策略有效降低了动平台的位姿误差。最后,通过实验验证了刚度模型与力/位混合控制策略的准确性和有效性。

轮足混合式移动机器人动力转向系统

为提高轮足混合式移动机器人的路面适应能力,设计一种新的动力转向系统。分析传统动力转向装置无法应用于轮足混合式机器人的原因,并做出问题描述;给出新型动力转向系统的设计要求并提供一种新型动力转向系统的结构;描述该系统可以实现的功能。结果表明:该系统能解决传统动力转向系统不能使车轮大幅度升降的问题,对未来转向系统的设计提供借鉴。

Analysis of the constraint relation between ground and self-adaptive mobile mechanism of a transformable wheel-track robot

To maneuver in unstructured terrains where the ground might be soft, hard, flat or rough, a transformable wheel-track robot (NEZA-I) with a self-adaptive mobile mechanism is proposed and developed. The robot consists of a control system unit, two symmetric transformable wheel-track (TWT) units, and a rear-wheel unit. The TWT unit is the main mobile mechanism for the NEZA-I robot, with the rear-wheel unit acting as an assistant mechanism. Driven only by one servomotor, each TWT unit can efficiently select between track mode and wheel mode for optimal locomotion, autonomously switching locomotion mode and track configuration with changes in the terrain. In this paper, the mechanism structure, the self-adaptive drive system, the locomotion mode and posture of the NEZA-I robot are presented, the kinematic relation of the inside parts of the TWT unit is analysed, and the mathematic model of the constraint relation between the mobile mechanism and the ground, abbreviated to "MGCR model" is set up for the NEZA-I robot to go through some typical unstructured environments. The mechanism parameters, which influence the self-adaptability of the NEZA-I robot, are found and optimized. Basic experiments show that the mobile mechanism has the self-adaptability to navigate in unstructured terrains and has superior obstacle-negotiating performance, and that the MGCR model and the analysis method of mechanism parameters are reasonable. From a mechanism point of view, it can provide an idea for research on the adaptive control of the robot.

自主轮式移动机器人CASIA-I的整体设计

详细介绍了我们自行设计、研制的一种室内移动机器人CASIA-I,及其移动机构、电子系统和基于智能体(Agent)的混合型体系结构。该平台良好的开放性、可扩展性和稳定性,为用户的二次开发提供了保证。

基于虚拟力的混合感知网节点部署

感知网一般是由静态的或移动的节点组成,为保证感知网的感知功能,节点应该有自部署和自修复能力.然而全部由移动传感器组成的感知网的成本太高,为保证感知网的覆盖功能和低成本,提出了一种在静态传感器节点中加入移动传感器节点的混合感知网形式.为了更好地部署这些节点,最大化覆盖待感知区域,提出了一种基于节点间虚拟力的移动节点部署方法,利用静态节点和移动节点以及移动节点之间的虚拟人工势场产生的作用力来控制移动节点的运动,使移动节点能够在较短的时间内,以较少的能量消耗到达自己合适的位置.在理论上分析了算法的可行性,用仿真实验验证了此算法的有效性,并和其他3种类似算法进行了性能比较.

一种改进量子行为粒子群优化算法的移动机器人路径规划

为实现移动机器人最优路径规划,提出了一种改进量子行为粒子群的优化算法(LTQPSO)。针对粒子群算法存在过早收敛的问题,利用个体粒子进化速度与群体离散度来动态调整惯性权重,使惯性权重具有自适应性与控制性,从而避免过早收敛;同时将自然选择方法引入传统位置更新公式中,以保持种群的多样性,加强LTQPSO算法的全局搜索能力,加快算法的收敛速度;将改进后的LTQPSO算法应用于移动机器人路径规划中;最后通过理论仿真与移动机器人平台实验验证了该方法的有效性与可行性。

改进QPSO和Morphin算法下移动机器人混合路径规划

为了提高机器人在复杂环境下路径规划的能力,提出了一种基于改进量子粒子群优化算法(QPSO)和Morphin算法的混合路径规划方法。利用栅格地图建立环境模型并确定起始点和目标点,通过引入自适应局部搜索策略和交叉操作对QPSO进行改进规划出一条最优的全局路径,机器人根据全局路径行走,当发现未知静态或动态障碍物立即调用Morphin算法进行局部路径规划,避开障碍物后回到原全局路径上继续行走至目标点。该混合路径规划方法的有效性和可行性通过Matlab仿真和实际应用得到很好地验证。