一种小型陆空两栖机器人的选型分析与结构设计

为了适应灾害救援、资源勘探、野外侦查等复杂作业、复杂场景、复杂地形产生的特殊需求,文章研究了一种小型陆空两栖机器人的总体构型及其结构设计。首先根据该机器人要能实现陆地低角度侦查和空中高角度侦查的使用需求,确定该机器人要兼具地面运动能力和空中运动能力,其功能是地面机器人和飞行机器人的有机结合,据此分别探讨了一体式和组合式两种设计方案,进行了机构的构型分析[1]。在一体式构型方案中,对两自由度结构腿和三自由度结构腿分别进行了阐述与分析。最后综合对比了一体式构型方案和组合式构型方案,通过对优缺点的综合对比,得出组合式构型方案在功能性、实用性和稳定性等方面具有明显优势,为该机器人物理样机的研制提供了可靠、可信的依据[2]。     

Iterative path-accurate trajectory generation for fast sensor-based motion of robot arms

Sensor-based trajectory generation of industrial robots can be seen as the task of, first, adaptation of a given robot program according to the actually sensed world, and second, its modification that complies with robot constraints regarding its velocity, acceleration, and jerk. The second task is investigated in this paper. Whenever the sensed trajectory violates a constraint, a transient trajectory is computed that, both, keeps the sensed path, and reaches the sensed trajectory as fast as possible while satisfying the constraints. This is done by an iteration of forward scaling and backtracking. In contrast to previous papers, a new backtracking algorithm and an adaptation of the prediction length are presented that are favorable for high-speed trajectories. Arc Length Interpolation is used in order to improve the path accuracy. This is completed by provisions against cutting short corners or omitting of loops in the given path. The refined trajectory is computed within a single sampling step of 4 ms using a standard KUKA industrial robot.     

Design improvements and control of a hybrid walking robot

In this paper design improvements and control algorithms are presented for a 2-DOF (Degree-Of-Freedom) hybrid leg-wheel walking machine. A prototype of a low-cost robot, which is capable of straight walking and steering with only two actuators, has been designed and built at LARM: Laboratory of Robotics and Mechatronics in Cassino. A control system has been developed in order to control the robot’s operation and to improve the prototype’s behavior. The designed control system and simulation results have been reported to show the operation of the prototype.     

Sensor-based robot motion generation in unknown, dynamic and troublesome scenarios

A sensor-based motion control system was designed to autonomously drive vehicles free of collisions in unknown, troublesome and dynamic scenarios. The system was developed based on a hybrid architecture with three layers (modeling, planning and reaction). The interaction of the modules was based on a synchronous planner–reactor configuration where the planner computes tactical information to direct the reactivity. Our system differs from previous ones in terms of the choice of the techniques implemented in the modules and in the integration architecture. It can achieve robust and reliable navigation in difficult scenarios that are troublesome for many existing methods. Experiments carried out in these scenarios with a real vehicle confirm the effectiveness of this technique.     

Design of a large-scale cable-driven robot with translational motion

The design of a new cable-driven robot for large-scale manipulation is presented with focus on the tension condition in the cables. In this robot, the arrangement of the cables is such that the moving platform has three translational motions. The robot has potentials for large-scale robotic manipulations, machining of large parts and material handling. The design analysis presented here is towards the synthesis of the robot as well as the sizing of the actuators and cables. The synthesis of this robot is dependent on the results of the tensionable workspace analysis previously published by the Alikhani et al. [6]. The analysis of the cable forces is presented in detail, which is then used to size the actuators. For this purpose, a geometrical approach is used to represent the capability of the end-effector for applying forces and moments as convex polyhedra. The design problem is then reduced to the sizing of these polyhedra according to the design requirements and manufacturing limitations. A prototype is also designed and fabricated, which is presented at the end to further elaborate on the proposed approach.     

Acquisition of obstacle motion patterns to improve mobile robot motion planning

Mobile robots for advanced applications have to act in environments which contain moving obstacles (humans). Even though the motions of such obstacles are not precisely predictable, usually they are not completely random; long-term observation of obstacle behavior may thus yield valuable knowledge about prevailing motion patterns. By incorporating such knowledge as statistical data, a new approach called statistical motion planning yields robot motions which are better adapted to the dynamic environment. To put these ideas into practice, an experimental system has been developed. Cameras observe the workspace in order to detect obstacle motion. Statistical data is derived and represented as a set of stochastic trajectories. This data can be directly employed in order to calculate collision probability, i.e. the probability of encountering an obstacle during the robot's motion. Further aspects of motion planning are addressed: path planning which minimizes collision probability, estimation of expected time to reach the goal and reactive planning.     

Design and control of a climbing robot based on hot melt adhesion

Robust climbing in unstructured environments has been one of the long-standing challenges in robotics research. Among others, the control of large adhesion forces is still an important problem that significantly restricts the locomotion performance of climbing robots. The main contribution of this paper is to propose a novel approach to autonomous robot climbing which makes use of hot melt adhesion (HMA). The HMA material is known as an economical solution to achieve large adhesion forces, which can be varied by controlling the material temperature. For locomotion on both inclined and vertical walls, this paper investigates the basic characteristics of HMA material, and proposes a design and control of a climbing robot that uses the HMA material for attaching and detaching its body to the environment. The robot is equipped with servomotors and thermal control units to actively vary the temperature of the material, and the coordination of these components enables the robot to walk against the gravitational forces even with a relatively large body weight. A real-world platform is used to demonstrate locomotion on a vertical wall, and the experimental result shows the feasibility and overall performances of this approach.     

动力学解析的四轮全向移动机器人电机解耦控制

四轮全向移动机器人是一个复杂的非线性、强耦合的机械系统,各轮驱动电机间存在强耦合现象,很难取得理想的控制效果。针对这一问题,提出一种基于动力学解析的多电机控制系统解耦方法。通过对四轮机器人的动力学解析推导出四轮转速与其驱动力矩间的状态方程,获得各电机输入输出量之间的耦合关系,在此基础上依据控制量一致思想设计解耦控制器,解决了传统参考模型解耦方法不能兼顾控制性能和解耦性能的问题,实现了四路电机的独立控制。仿真结果显示,该方法能够有效地减小控制系统各变量间的相互耦合作用,每路电机均很好地跟踪了各自的输入,解耦效果好。     

Investigation of the motion of a vibration-driven robot on a vertical ferromagnetic surface

A mathematical model of the motion of a vibration-driven robot on a vertical metallic surface due to an adhesive electromagnetic device and rotation of unbalanced masses built into the robot’s body is constructed. The motion principle is described in detail and a design scheme of the robot is presented. As a result of computational experiments, the laws of the robot’s motion are established. The parameters that most affect the motion are determined.     

基于S3C44BOX和SM5004的足球机器人运动控制系统

Robocup中型组的足球机器人控制系统设计。描述了以S3C44BOX为主控芯片,SM5004为驱动芯片的底层运动控制模块的硬件结构,通过分析四轮全向机器人的运动学模型,使用模糊自适应PID控制算法完成对机器人的闭环控制。实践证明,以这种控制器作为ROBOCUP中型组机器人的底层运动控制系统,其速度、位置及控制精度等指标均达到了设计要求。     

Remedy scheme and theoretical analysis of joint-angle drift phenomenon for redundant robot manipulators

A quadratic programming (QP)-based method, as a remedy for joint angle drifts, is employed for redundant robot manipulators with physical constraints (e.g., joint-angle limits and joint-velocity limits) considered. By using the QP-based redundancy-resolution scheme, real-time repetitive motion planning (RMP) can be achieved in a drift-free manner. Theoretical analyses based on gradient-descent and neural-dynamic methods are also conducted. Based on analyses, the efficacy of the presented QP-based RMP scheme for redundant manipulators is successfully explained. To demonstrate the effectiveness of the RMP scheme, different kinds of redundant robot manipulators, such as PA10, PUMA560, and a six-link planar robot arm, are tested in order to perform circular and straight line end-effector trajectories by using computer simulations. Both theoretical analysis and computer simulation results have demonstrated the efficacy of the QP-based RMP scheme.     

Graphic-based analysis of robot motion economy principles

Performance of robotic systems depends on the robot design, its motions and the workcell set-up. Robot motion economy principles can provide important design guidelines to optimize the overall automation in robotic work systems. This work presents graphic-based analysis of the performance of 10 different robots in four classes and three group sizes for 27 different bin locations (positions and orientations). This extensive analysis and evaluation lead to several conclusive results concerning motion economy principles related to design of robotic workcells.     

全柔性铰链平面并联微动机器人的有限元分析

介绍了并联机器人的特点及其应用,对全柔性铰链平面并联机器人建立了刚性模型,并采用闭环线型原理建立理论运动学线性模型（Jacobian矩阵）,用ANSYS软件对其进行有限元分析,得到有限元运动学模型（Jacobian矩阵值）,讨论两者关系,发现有限元模型比理论模型要精确.     

Capsule-type vibration-driven robot with an electromagnetic actuator and an opposing spring: Dynamics and control of motion

A model of a mobile capsule robot that consists of the housing and internal body is considered. The internal body can move relative to the housing along a straight line. The internal body is attached to the housing by a spring. The system motion is excited by a force that acts between the housing and the internal body. The force changes in a pulse-width periodic mode. The robot’s motion along a straight line on a rough horizontal plane is investigated. It is assumed that the dry Coulomb friction acts between the housing and the plane. The dependence of the average steady state robot velocity on excitation parameters is analyzed. It is established that it is possible to control the magnitude and direction of the robot motion by changing the period and the duty cycle of the pulse-width excitation signal. The effect of the variation in the direction of the robot motion due to changing the excitation period is observed. This effect is associated with the phenomenon of resonance.     

Design and experimental validation of a second-order sliding-mode motion controller for robot manipulators

This article presents an original motion control strategy for robot manipulators based on the coupling of the inverse dynamics method with the so-called second-order sliding mode control approach. Using this method, in principle, all the coupling non-linearities in the dynamical model of the manipulator are compensated, transforming the multi-input non-linear system into a linear and decoupled one. Actually, since the inverse dynamics relies on an identified model, some residual uncertain terms remain and perturb the linear and decoupled system. This motivates the use of a robust control design approach to complete the control scheme. In this article the sliding mode control methodology is adopted. Sliding mode control has many appreciable features, such as design simplicity and robustness versus a wide class of uncertainties and disturbances. Yet conventional sliding mode control seems inappropriate to be applied in robotics since it can generate the so-called chattering effect, which can be destructive for the controlled robot. In this article, this problem is suitably circumvented by designing a second-order sliding mode controller capable of generating a continuous control law making the proposed sliding mode controller actually applicable to industrial robots. To build the inverse dynamics part of the proposed controller, a suitable dynamical model of the system has been formulated, and its parameters have been accurately identified relying on a practical MIMO identification procedure recently devised. The proposed inverse dynamics-based second-order sliding mode controller has been experimentally tested on a COMAU SMART3-S2 industrial manipulator, demonstrating the tracking properties and the good performances of the controlled system.     

Matching point features under small nonrigid motion

This paper describes a method for matching point features between images of objects that have undergone small nonrigid motion. Feature points are assumed to be available and, given a properly extracted set of feature points, a robust matching is established under the condition that the local nonrigid motion of each point is restricted to a circle of radius δ, where δ is not too large. This is in contrast to other techniques for point matching which assume either rigid motion or nonrigid motion of a known kind. The point matching problem is viewed in terms of weighted bipartite graph matching. In order to account for the possibility that the feature selector can be imprecise, we incorporate a greedy matching strategy with the weighted graph matching algorithm. Our algorithm is robust and insensitive to noise and missing features. The resulting matching can be used with image warping or other techniques for nonrigid motion analysis, image subtraction, etc. We present our experimental results on sequences of mammograms, images of a deformable clay object and satellite cloud images. In the first two cases we provide quantitative comparison with known ground truth.     

多移动机器人系统运动协调研究综述

运动协调是多移动机器人系统领域的主要研究热点之一。在阐述多机器人合作与运动协调两者关系的基础上,给出了多机器人系统运动协调的问题描述及其分类;从主要研究方法的角度,归纳总结了多机器人系统运动协调的国内外研究动态。最后,对运动协调在多移动机器人系统领域的前景和研究方向作出了展望。     

双臂空间机器人协调操作运动控制仿真系统的设计与实现

阐述了双臂自由飞行空间机器人闭链式协调操作运动控制实验平台的建立方法。将VC 6.0、OpenGL、Matlab和Matcom四种软件融合起来,搭建FFSR(自由飞行空间机器人)系统实验平台;通过运动控制算法描述了机器人双臂协调操作目标物的动态特性,给出了机器人本体中心的位置姿态和转角的变化曲线,验证了该运动控制算法的正确性,以及编程效率的优越性。     

Learning object deformation models for robot motion planning

In this paper, we address the problem of robot navigation in environments with deformable objects. The aim is to include the costs of object deformations when planning the robot’s motions and trade them off against the travel costs. We present our recently developed robotic system that is able to acquire deformation models of real objects. The robot determines the elasticity parameters by physical interaction with the object and by establishing a relation between the applied forces and the resulting surface deformations. The learned deformation models can then be used to perform physically realistic finite element simulations. This allows the planner to evaluate robot trajectories and to predict the costs of object deformations. Since finite element simulations are time-consuming, we furthermore present an approach to approximate object-specific deformation cost functions by means of Gaussian process regression. We present two real-world applications of our motion planner for a wheeled robot and a manipulation robot. As we demonstrate in real-world experiments, our system is able to estimate appropriate deformation parameters of real objects that can be used to predict future deformations. We show that our deformation cost approximation improves the efficiency of the planner by several orders of magnitude.