仿生机器蛇的设计

文章主要描述仿生机器蛇的设计,包括机器蛇的结构设计和运动规划连贯动作的实现。通过对蛇形机器人在有障碍物和无障碍物环境中,进行不同连贯动作的运动规划和运动形式变化,找出机器人设计的不同侧重点;最后,将对本文的不足和实验时所遇到的困难进行总结,并加以展望。     

Multiple Traveling Robot Problem: A Solution Based on Dynamic Task Selection and Robust Execution

The multiple traveling robot problem (MTRP), the real-world version of the well-known NP-hard multiple traveling salesman problem (MTSP), asks for finding routes of robots to visit a set of targets. Various objectives may be defined for this problem (e.g., minimization of total path length, time, etc.). The overall solution quality is dependent on both the quality of the solution constructed by the paths of robots and the efficient allocation of the targets to robots. Unpredictability of the exact processing times of tasks, unstable cost values during execution, and inconsistencies due to uncertain information further complicate MTRP. This paper presents a multirobot cooperation framework employing a dynamic task selection scheme to solve MTRP. The proposed framework carries out an incremental task allocation method that dynamically adapts to current conditions of the environment, thus handling diverse contingencies. Globally efficient solutions are obtained through mechanisms that result in the allocation of the most suitable tasks from dynamically generated priority-based rough schedules. Since the presented approach is for real-world task execution, computational requirements are kept at a minimum, and the framework is designed to be applicable on real robots even with limited capabilities. The efficiency and the robustness of the proposed scheme is evaluated through experiments both in simulations and on real robots.     

An exoskeletal robot for human shoulder joint motion assist

We develop exoskeletal robots to assist the motion of physically weak persons such as elderly persons or handicapped persons. In our previous research (2001), a prototype of a two degree of freedom exoskeletal robots for shoulder joint motion assist have been developed. In this paper, we propose an effective fuzzy-neuro controller, a moving mechanism of the center of rotation (CR) of the shoulder joint of the exoskeletal robot, and an intelligent interface in order to realize a practical and effective exoskeletal robot for shoulder joint motion assist. The fuzzy-neuro controller enables the robot to assist a person's shoulder motion. The moving mechanism of the CR of the robot shoulder joint is used to fit the CR of the robot shoulder joint to that of the physiological human shoulder joint during the shoulder motion. The intelligent interface is realized by applying a neural network and used to cancel out the effect the human subject's arm posture change. The effectiveness of the proposed method was evaluated by experiment.     

Optimal control at energy performance index of the mobile robots following dynamically created trajectories

In practice, the problem of motion control of the wheeled mobile robots is often neglected. Wheeled mobile robots are strongly nonlinear systems and restricted by non-holonomic constraints. Motion control of such systems is not trivial task and usage of non-optimal control signals can lead to deterioration of the overall robot system's performance. In case of autonomous application of the mobile robots all parts of its control system should work perfectly. The paper presents the theory and application of the optimal control method at the energy performance index towards motion control of the two-wheeled mobile robot during the realisation of complex, dynamically created trajectories. With the use of the proposed control method the two-wheeled mobile robot can realise effectively the desired trajectory, which is generated ad-hoc by the navigation system of the robot. Thus the proposed method can be used for motion control of autonomous or semi-autonomous wheeled mobile robots. The presented results of both computer simulations and experiments indicate that the proposed method works effectively from the point of view of the motion control of two-wheeled mobile robot. Movement of the mobile robot appeared reliable and predictable during all the tests.     

一种机载SAR快速几何精校正算法

几何定位精度是SAR在遥感测绘领域的一个重要技术指标。机载SAR具备高机动性、高分辨率、低成本等方面的优势,是SAR技术发展的一个重要方向。运动误差和地形起伏是机载SAR几何定位的重要误差来源。该文从SAR成像原理和成像几何的角度出发,深入研究了运动误差与地形起伏耦合下几何定位误差的产生机理,并在此基础上提出了一种快速几何精校正方法。仿真实验和实测数据结果验证了该方法的正确性和有效性。      

CPG-based control of serpentine locomotion of a snake-like robot

In this paper, a biomimetic approach is proposed to solve the difficulty in control of a snake-like robot with a large number of degrees of freedom. This method is based on the central pattern generator (CPG), which is a rhythmical motion generator existing in most animals. Compared with the previous research, a new network with feedback connection is presented, which can generate uniform outputs without any adjustment. Furthermore, the relation characteristics between the CPG parameters and the outputs are investigated. Both simulation and experiment of the snake-like robot have been taken for the analysis of the locomotion control. Desired locomotion patterns can be achieved by adjusting the CPG parameters correspondingly from the results.     

PSD – probabilistic algorithm for mobile robot 6D localization without natural and artificial landmarks based on 2.5D map and a new type of laser scanner in GPS-denied scenarios

This paper presents an approach to mobile robot 6D localization based on a 3D laser scanner in GPS-denied scenarios. Commonly, 6D localization using laser scanners is performed with the use of extraction and association of the features or by comparison of the whole scans (very often off-line) using the ICP algorithm or its modifications. However, in some unstructured non-urbanized rough terrain environments, feature extraction does not seem to be reliable enough. For such kind of environment, we present a new method to mobile robot localization in GPS-denied applications, called PSD (Point-to-Surfel Distance). Unlike state of the art localization methods using laser scanners, we consider every single laser scanner measurement as an observation and use Point-to-Surfel Distance for correction of position and orientation of the robot. Mobile robot localization is based on a specific representation of the terrain in the 2.5D surfel map (terrain height and inclination). The simulation tests compared our method using extended Kalman filter (EKF) and single laser scanner measurements with an up-to-date method using particle filter (PF) and comparing the scan lines with the reference map and with another method using Gaussian mixture maps. The tests confirmed that the proposed method provides satisfying results for GPS-denied scenarios in rough terrain without extractable landmarks and our method is thirty times faster than the PF method (serial implementation). KITTI benchmark tests and real terrain experiments confirmed its usefulness and advantages as well.     

Movement control algorithms for realization of fault-tolerant ad hoc robot networks

Autonomous and semi-autonomous mobile multirobot systems require a wireless communication network in order to communicate with each other and collaboratively accomplish a given task. A multihop communications network that is self-forming, self-healing, and self-organizing is ideally suited for such mobile robot systems that exist in unpredictable and constantly changing environments. However, since every node in a multihop (or ad hoc) network is responsible for forwarding packets to other nodes, the failure of a critical node can result in a network partition. Hence, it is ideal to have an ad hoc network configuration that can tolerate temporary failures while allowing recovery. Since movement of the robot nodes is controllable, it is possible to achieve such fault-tolerant configurations by moving a subset of robots to new locations. In this article we propose a few simple algorithms for achieving the baseline graph theoretic metric of tolerance to node failures, namely, biconnectivity. We formulate an optimization problem for the creation of a movement plan while minimizing the total distance moved by the robots. For one-dimensional networks, we show that the problem of achieving a biconnected network topology can be formulated as a linear program; the latter lends itself to an optimal polynomial time solution. For two-dimensional networks the problem is much harder, and we propose efficient heuristic approaches for achieving biconnectivity. We compare the performance of the proposed algorithms with each other with respect to the total distance moved metric using simulations.     

多机器人定位中基于熵的分布式观测量选择方法

本文提出了多机器人定位中基于熵的分布式观测量选择新方法.在多机器人基于相对观测量的合作定位中,当队列中某个机器人在某时刻获得多个相对观测量时,我们可以融合所有这些观测来更新整个队列的位置及协方差矩阵.但随着机器人个数及观测量的增加,定位计算量将迅速增长,影响了定位的实时性和有效性.为了减轻计算负担、保持定位的实时性,首先对这些观测量进行选择,找出那些具有大的信息量的观测,利用这些观测量来更有效的更新整个队列的位置及协方差矩阵.在保证一定定位精度的前提下,减少了整个队列定位的计算量,提高了定位的实时性和可靠性.我们研究比较了在选择不同数量的观测量的条件下,定位精度和定位时间的变化.仿真实验结果表明,基于熵的分布式观测量选择方法可有效地提高定位的效率,尤其是在机器人个数比较多的情况下,更能显示它的优势.     

A Multidirectional Locomotion Light-Driven Soft Crawling Robot

Soft robots based on bionics with multi-freedom and communication abilities have attracted extensive attention in recent years. However, the solutions for soft robots with multidirectional locomotion currently concentrate on complex drive modes and exhibit application unfriendliness. In this work, an untethered multidirectional locomotion light-driven soft crawling robot is proposed with the integration of communication module, which can traverse in four directions with a fixed near-infrared (NIR) light source and is also capable of positioning and perception. Owing to the photothermal response of graphene oxide and ingenious structural design, the critical states of robot deformation can be determined simply by controlling the duration of NIR light, ultimately resulting in different crawling directions. Furthermore, a communication module is integrated into the robot enabling the robot to locate and sense humidity by magnetic coupling. The proposed robot provides an innovative strategy for the design and integration of multidirectional locomotion soft crawling robots, showing great potential in intelligent robots.     

Mobile Robot Exploration in Indoor Environment Using Topological Structure with Invisible Barcodes

This paper addresses the localization and navigation problem in the movement of service robots by using invisible two dimensional barcodes on the floor. Compared with other methods using natural or artificial landmarks, the proposed localization method has great advantages in cost and appearance since the location of the robot is perfectly known using the barcode information after mapping is finished. We also propose a navigation algorithm which uses a topological structure. For the topological information, we define nodes and edges which are suitable for indoor navigation, especially for large area having multiple rooms, many walls, and many static obstacles. The proposed algorithm also has the advantage that errors which occur in each node are mutually independent and can be compensated exactly after some navigation using barcodes. Simulation and experimental results were performed to verify the algorithm in the barcode environment, showing excellent performance results. After mapping, it is also possible to solve the kidnapped robot problem and to generate paths using topological information.     

A novel 3D path following control framework for robots performing surface finishing tasks

We describe a novel 3D path following control framework for articulated robots in applications where constant speed travel along a path is desirable, such as robotic surface finishing tasks. Given the desired robot configuration sequence with a list of waypoints along a path, a trajectory optimization scheme based on direct collocation is proposed to determine the Cartesian path and the maximum constant translation speed that are dynamically feasible. Employing the Hermite–Simpson collocation method, a Cartesian path is developed that not only preserves the characteristics of the original motion sequence but also satisfies the physical requirements of the robot kinematics and dynamics. Since joint velocity control is quite common in many industrial robots, we consider a 3D kinematic control in the robot tool frame with control inputs as rate of change of orientation. The objective for the translation motion is to achieve constant speed along the path tangent direction, and that of the orientation control is to orient the robot properly based on the path provided by a converging path planner. We describe the optimization procedure employed with the direct collocation method to obtain the desired Cartesian path, an arc-length based re-parametrization of the desired path, and a path planner that provides a converging path to the desired path. To perform the surface finishing operation, we further present the joint space control law that is converted from the synthesis of the proposed path following and impedance force control in the tool frame. To verify and evaluate the performance of the proposed framework, we have conducted extensive experiments with a six degrees-of-freedom (DOF) industrial robot for several paths that can be employed for surface finishing of a variety of industrial parts.     

基于LabVIEW的手术机器人虚拟仿真平台设计

为了清晰地观察手术机器人的运动状态,文中提出了一种基于LabVIEW的3D虚拟仿真平台构建方法。该方法将图形化编程软件LabVIEW作为构建平台,结合SolidWorks机械建模、LabVIEW的GUI前面板、三维显示控件以及LabVIEW Robotics工具包搭建了可视化程度高、模型效果逼真的手术机器人3D虚拟仿真平台。针对文中设计里自主构建的从手机械臂和主手操作台,详细讲述了虚拟仿真平台的构建过程,并且使用算法实现了手术机器人在主从控制系统中的实时参数控制。最后结合MATLAB对手术机器人末端位置运动进行测试对比。测试结果表明轨迹路径一致,可以通过该方法实现对手术机器人的虚拟仿真平台构建。     

Adaptive impedance control with variable target stiffness for wheel-legged robot on complex unknown terrain

Wheel-legged robots operating on the ground experience real-time interactions with the complex unknown terrain, which may lead to tilting of the whole body and instability if no regulated effort is made. Maintaining a horizontal posture of the whole body with changes in the terrain geometry via impedance control (IC) that is widely used in many fields is desirable to be realized. However, because the stiffness and location of the terrain relative to the robot are not known in advance, the force-tracking error occur when using IC, which is the main cause of robot tilting. In this paper, an adaptive variable impedance control (AVIC) method is proposed to minimize the force-tracking error for the forces of each leg that are exerted on the body, thereby maintaining a horizontal posture of the whole body and improving the stability. This control method is applied by adjusting the target stiffness to compensate for terrain uncertainties. In terms of the existence of the dynamic force tracking error, the proposed control method also allows the robot to adapt to changes to track the desired force. The theoretical analysis of the stability of the AVIC was demonstrated through a stable force-tracking application. The numerical and experimental results were compared to those obtained using IC, and the proposed control method was validated on complex, unknown terrain.     

Complete coverage navigation of cleaning robots using triangular-cell-based map

This paper presents a novel approach for navigation of cleaning robots in an unknown workspace. To do so, we propose a new map representation method as well as a complete coverage navigation method. First, we discuss a triangular cell map representation which makes the cleaning robot navigate with a shorter path and increased flexibility than a rectangular cell map representation. Then, we propose the complete coverage navigation and map construction methods which enable the cleaning robot to navigate the complete workspace without complete information about the environment. Finally, we evaluate the performance of our proposed triangular cell map via the existing distance-transform-based path-planning method comparing it to that of the rectangular cell map. Also, we verify the effectiveness of the proposed methods through computer simulations.     

Lightweight digital video stabilization for small-size robot

Though constrained by payload and processing, small robots have gained applications in collecting visual information from the scene. Typically these small-size robots do not carry data loggers and send the video information to a hand-held device at a remote location for visual observations. Due to sophisticated processing and control limitations from mechatronics resources, the video captured by the robot is subjected to the effects of unintended motion, which requires digital methods for video stabilization. For a lightweight solution for video stabilization, we avoid use of any external hardware and develop a Singular Value Decomposition (SVD) based digital algorithm that avoids explicit feature tracking and motion estimation during stabilization. The process involves identifying a subspace with minimal dimensions that contains information of intentional motion alone. This work identifies the minimal subspace for video stabilization using the sliding window geometry method for practical implementation. Further, a shape-preserving filter is utilized to remove perturbations induced by the unintended motions, thereby resulting in the reconstruction of the stabilized video sequence. Experimental results on two different small-size robots viz spherical robot and Unmanned Aerial Vehicle (UAV) in indoor and outdoor settings, respectively, show quality outcomes without any change in parameters of the proposed filter design. Performance comparison with existing methods on the quality of stabilized video shows that the proposed stabilization method overcomes the non-availability of features for tracking due to large amplitudes and limited onboard resources. With the proposed video stabilization method, there is a potential for wider applicability of small-size robots in remote visual observations.     

自恢复蒙特卡罗定位算法

机器人定位技术作为智能机器人领域的重要技术,是机器人进行自主规划和导航的重要前提。为解决机器人运动过程中的绑架问题,在蒙特卡罗定位(Monte Carlo localization, MCL)算法的基础上,提出了基于激光雷达似然域模型的定位可靠度评判算法以及基于惯性导航单元的定位自恢复模型。定位可靠度评判算法对机器人是否发生绑架问题进行判定,当发生绑架问题后,首先基于惯性导航单元的测量数据进行位姿预估计,然后基于预估计的位姿构建粒子重分布模型,最后进行粒子滤波得到重定位的结果,达到了对机器人绑架判定和自恢复定位的目的。经过实验测试和对比,该算法可以对绑架问题进行高效的判断,具有更高的恢复效率和准确度。     

Multi-hierarchy interaction control of a redundant robot using impedance learning

The control of robots with a compliant joint motion is important for reducing collision forces and improving safety during human robot interactions. In this paper, a multi-hierarchy control framework is proposed for the redundant robot to enable the robot end-effector to physically interact with the unknown environment, while providing compliance to the joint space motion. To this end, an impedance learning method is designed to iteratively update the stiffness and damping parameters of the end-effector with desired performance. In addition, based on a null space projection technique, an extra low stiffness impedance controller is included to improve compliant joint motion behaviour when interaction forces are acted on the robot body. With an adaptive disturbance observer, the proposed controller can achieve satisfactory performance of the end-effector control even with the external disturbances in the joint space. Experimental studies on a 7 DOF Sawyer robot show that the learning framework can not only update the target impedance model according to a given cost function, but also enhance the task performance when interaction forces are applied on the robot body.     

Multi‐robot Mapping Using Omnidirectional‐Vision SLAM Based on Fisheye Images

This paper proposes a global mapping algorithm for multiple robots from an omnidirectional‐vision simultaneous localization and mapping (SLAM) approach based on an object extraction method using Lucas–Kanade optical flow motion detection and images obtained through fisheye lenses mounted on robots. The multi‐robot mapping algorithm draws a global map by using map data obtained from all of the individual robots. Global mapping takes a long time to process because it exchanges map data from individual robots while searching all areas. An omnidirectional image sensor has many advantages for object detection and mapping because it can measure all information around a robot simultaneously. The process calculations of the correction algorithm are improved over existing methods by correcting only the object's feature points. The proposed algorithm has two steps: first, a local map is created based on an omnidirectional‐vision SLAM approach for individual robots. Second, a global map is generated by merging individual maps from multiple robots. The reliability of the proposed mapping algorithm is verified through a comparison of maps based on the proposed algorithm and real maps.     

Mobility analysis of the typical gait of a radial symmetrical six-legged robot

Radial symmetrical hexapod robots have attracted the attention of the research community because of their flexibility. There is nonetheless still much to study on their kinematics, dynamics and locomotion. In this paper, initially, full body kinematics of a radial symmetrical six-legged robot with statically stable movements are reviewed. The kinematics analysis is made on cooperated swing legs over supporting legs. Using the robot screw theory and exponential product equations, the velocities and accelerations referring to the object reference frame of each robot part are presented in a compact form. This makes it easy to calculate kinetic energy and so to build the dynamics model using the Lagrangian method. Many ways of walking of six-legged robots have been introduced in specialized literature. However, mobility comparison is still open to research. Two main aspects of mobility are analyzed in detail in this paper. The first one concerns the mobility of three statically stable ways of walking (the insect-wave gait, mammal-kick gait and mixed gait) with the same duty factor on the same radial symmetrical hexapod robot. The stability, energy efficiency, turning flexibility, and terrain or environment adaptability among those gaits have been compared. The mixed gait presents important advantages over the other two, while those two are useful for some special terrain conditions where the mixed gait is limited. The second aspect that has been analyzed focuses on the mobility of the body. The body height, measured from the body bottom to the supporting surface, and the stride optimization factors are proposed according to the obstacles’ configuration and the energy optimization. The results of our study can be used for the intelligent locomotion control of some articulated multi-legged robots for walking statically-stably on a complicated surface.Most of our analyses have been successfully verified on the prototype which has been designed by Politecnico di Milano (POLIMI) and Beijing University of Astronautics and Aeronautics (BUAA) and developed by POLIMI in 2007.