Rolling and swaying motion estimation for a mobile robot by using omnidirectional optical flows

Described here is a method for estimating rolling and swaying motions of a mobile robot using optical flow. We have proposed an image sensor with a hyperboloidal mirror for the vision-based navigation of a mobile robot. Its name is HyperOmni Vision. The radial component of optical flow in HyperOmni Vision has a periodic characteristic. The circumferential component of optical flow has a symmetric characteristic. The proposed method makes use of these characteristic to estimate robustly the rolling and swaying motion of the mobile robot. Correspondence to: Y. Yagi e-mail: y-yagi@sys.es.osaka-u.ac.jp     

科氏流量计振动信号参数估计的最小二乘法

振动信号参数估计是科氏流量计振动控制和流量解算的基础。针对科氏流量计振动信号特征,基于最小二乘与函数逼近原理,提出一种适用于科氏流量计振动信号的参数估计方法。该方法利用FFT粗估计出信号频率,据此设定频率搜索区间,解最小二乘方程获得信号余弦幅度、正弦幅度和直流偏移,改变频率逐次逼近真值,使得误差平方和最小,最小误差平方和所对应参数即为参数估计值。仿真分析了估计精度和抗噪性能,对罗斯蒙特F200S型科氏流量计实测信号进行了参数分析与估计,结果表明了该方法估计的准确性和实用性。     

Accuracy analysis of bias-eliminating least squares estimates for errors-in-variables systems

The bias-eliminating least squares (BELS) method is one of the consistent estimators for identifying dynamic errors-in-variables systems. In this paper, we investigate the accuracy properties of the BELS estimates. An explicit expression for the normalized asymptotic covariance matrix of the estimated parameters is derived and supported by some numerical examples.     

Control of a nonholonomic mobile robot using an RBF network

This article deals with handling unknown factors, such as external disturbance and unknown dynamics, for mobile robot control. We propose a radial-basis function (RBF) network-based controller to compensate for these. The stability of the proposed controller is proven using the Lyapunov function. To show the effectiveness of the proposed controller, several simulation results are presented. Through the simulations, we show that the proposed controller can overcome the modelling uncertainty and the disturbances. The proposed RBF controller also outperforms previous work from the viewpoint of computation time, which is a crucial fact for real-time applications.This work was presented in part at the 8th International Symposium on Artificial Life and Robotics, Oita, Japan, January 24–26, 2003     

Stochastic adaptive control using a modified least squares algorithm

Recent papers on stochastic adaptive control have established global convergence for algorithms using a stochastic approximation iteration. However, to date, global convergence has not been established for algorithms incorporating a least squares iteration. This paper establishes global convergence for a slightly modified least squares stochastic adaptive control algorithm. It is shown that, with probability one, the algorithm will ensure that the system inputs and outputs are sample mean square bounded and the mean square output tracking error achieves its global minimum possible value for linear feedback control.     

Data‐based output feedback control using least squares estimation method for a class of nonlinear systems

This paper develops a data‐based output feedback control method for a class of nonlinear systems, which have unknown mathematical models. The dynamic model of the system is assumed to be smooth, while the corresponding Jacobian matrices are constant matrices in each sampling period. We employ a zero‐order hold and a fast sampling technique to sample and measure the output signal. When these measured data contain white noises, we use the least squares method to estimate the corresponding Jacobian matrices. The feedback gain matrix is calculated and adjusted adaptively in real time according to them. Theoretical analysis on the convergence condition is provided, and simulation results are used to demonstrate the feasibility of this method. Copyright © 2013 John Wiley & Sons, Ltd.     

Localization of a mobile robot based on an ultrasonic sensor using dynamic obstacles

In this article, we propose a localization scheme for a mobile robot based on the distance between the robot and moving objects. This method combines the distance data obtained from ultrasonic sensors in a mobile robot, and estimates the location of the mobile robot and the moving object. The movement of the object is detected by a combination of data and the object’s estimated position. Then, the mobile robot’s location is derived from the a priori known initial state. We use kinematic modeling that represents the movement of a robot and an object. A Kalman-filtering algorithm is used for addressing estimation error and measurement noise. Throughout the computer simulation experiments, the performance is verified. Finally, the results of experiments are presented and discussed. The proposed approach allows a mobile robot to seek its own position in a weakly structured environment. This work was presented in part at the 12th International Symposium on Artificial Life and Robotics, Oita, Japan, January 25–27, 2007     

Guidance of a mobile robot using an array of static cameras located in the environment

This paper presents a new proposal for positioning and guiding mobile robots in indoor environments. The proposal is based on the information provided by static cameras located in the movement environment. This proposal falls within the scope of what are known as intelligent environments; in this case, the environment is provided with cameras that, once calibrated, allow the position of the robots to be obtained. Based on this information, control orders for the robots can be generated using a radio frequency link. In order to facilitate identification of the robots, even under extremely adverse ambient lighting conditions, a beacon consisting of four circular elements constructed from infrared diodes is mounted on board the robots. In order to identify the beacon, an edge detection process is carried out. This is followed by a process that, based on the algebraic distance, obtains the estimated ellipses associated with each element of the beacon. Once the beacon has been identified, the coordinates of the centroids for the elements that make up the beacon are obtained on the various image planes. Based on these coordinates, an algorithm is proposed that takes into account the standard deviation of the error produced in the various cameras in ascertaining the coordinates of the beacon’s elements. An odometric system is also used in guidance that, in conjunction with a Kalman Filter, allows the position of the robot to be estimated during the time intervals required to process the visual information provided by the cameras.

Indoor navigation of a non-holonomic mobile robot using a visual memory

When navigating in an unknown environment for the first time, a natural behavior consists on memorizing some key views along the performed path, in order to use these references as checkpoints for a future navigation mission. The navigation framework for wheeled mobile robots presented in this paper is based on this assumption. During a human-guided learning step, the robot performs paths which are sampled and stored as a set of ordered key images, acquired by an embedded camera. The set of these obtained visual paths is topologically organized and provides a visual memory of the environment. Given an image of one of the visual paths as a target, the robot navigation mission is defined as a concatenation of visual path subsets, called visual route. When running autonomously, the robot is controlled by a visual servoing law adapted to its nonholonomic constraint. Based on the regulation of successive homographies, this control guides the robot along the reference visual route without explicitly planning any trajectory. The proposed framework has been designed for the entire class of central catadioptric cameras (including conventional cameras). It has been validated onto two architectures. In the first one, algorithms have been implemented onto a dedicated hardware and the robot is equipped with a standard perspective camera. In the second one, they have been implemented on a standard PC and an omnidirectional camera is considered.

Dynamic estimation of optical flow field using objective functions

Optical flow (image velocity) fields are computed and interpreted from an image sequence by incorporating knowledge of object kinematics. Linear and quadratic objective functions are defined by considering the kinematics, and the function parameters are estimated simultaneously with the computation of the velocity field by relaxation. The objective functions provide an interpretation of the dynamic scenes and, at the same time, serve as the smoothness constraints. The computation is initially based on measured perpendicular velocity components of contours or region boundaries which, due to the ‘aperture problem’, are theoretically not the true perpendicular velocity components. This difficulty is alleviated by introducing a dynamic procedure for the measurement of the perpendicular components. Experiments on using objective functions for synthetic and real images of translating and rotating objects generated velocity fields that are meaningful and consistent with visual perception.     

Design of a teaching pendant program for a mobile shipbuilding welding robot using a PDA

Teaching pendant is a handheld device by which a human can control a robot. The main functions of a teaching pendant are moving the robot, teaching it about the locations, running robot programs, and jogging the axes. A teaching pendant is usually connected to the robot by a cable. The cable connection and the size of the teaching pendant generally do not pose a problem when the robot controller is separate from the robot. However, a large teaching pendant connected by a cable is not suitable for a self-propelled mobile robot with an internal controller. This paper describes the communication network of a personal data assistant (PDA) as a wireless teaching pendant for a mobile shipbuilding welding robot with embedded controller system that welds and moves autonomously inside the double hull structure of a ship. A double hull is a closed structure that has only a few access holes. It is very difficult and dangerous to weld components inside a double hull structure because of fumes, poisonous gas, and high temperatures. Using a wireless teaching pendant has the following advantages: (1) there are no limits to the welding activities that can take place, (2) the safety level increases because no workers are in close proximity to the robot, (3) workers are far away from the dangerous environmental conditions, (4) it is possible to reduce the weight of the cable connected to the robot, and (5) it is possible to reduce the weight of the robot because of the reduced load of the teaching pendant and the cable. We demonstrate the functionality and performance capabilities of our wireless teaching pendant through field-testing experiments.     

Optimal design and workspace analysis of a mobile welding robot with a 3P3R serial manipulator

This paper presents the design optimization of a mobile welding robot based on the analysis of its workspace. A welding robot has been developed to be used inside the double-hull structure of ships, and it shows good welding functionality. But there is a need to optimize the kinematic variables ensuring that the required welding functions inside the ships are satisfied. The task-oriented workspace, which is the workspace enabling specific rotations, has been defined in order to validate the welding ability of the robot, and incorporating the required rotational capabilities. To calculate the workspace, a geometric approach is adopted which considers the pitching and yawing angles simultaneously. Based on the workspace analysis, a scenario is compiled for considering a mass reduction, and a ratio between the design parameters and the workspace, with constraints on the workspace margins. The proposed optimization procedure is composed of two steps of coarse and fine searching. In the coarse searching step, a feasible parameter region (FPR) is defined, which satisfies the geometrical design constraints, and can be obtained without any considerations of the objective functions. In the fine searching step, the design parameters are determined by using the optimization technique of the conjugate gradient method in the overall FPRs. The suggested approach to calculating the task-oriented workspace, and the procedure of optimal design, are expected to be applied to general industrial robots.     

Region with velocity constraints: map information and its usage for safe motion planning of a mobile robot in a public environment

Recently, various autonomous mobile robots have been developed for practical use. To support the coexistence of robots and humans in real environments, we propose a concept named ‘Region with Velocity Constraints (RVC),’ which is set around hazardous areas. RVCs are regions where the velocities of the robot are constrained to predefined values. Inside the RVCs, the robot has to reduce its translational velocity to avoid predicted hazards such as collisions with obstacles, and to reduce its rotational velocity to prevent undesirable motions such as sharp turns. We also propose a motion planning method for navigating the mobile robot in an environment with RVCs based on the Navigation Function and Global Dynamic Window Approach. Our method generates a trajectory satisfying both translational and rotational velocity constraints to be compatible with the surroundings. Moreover, to demonstrate the validity of our method, we performed numerical simulations and experiments.     

Developing a design support system for the exterior form of running shoes using partial least squares and neural networks

The function of sport shoes is to improve sport performance and reduce sports-related injuries. They are commercial products developed by combining sports technology and marketing activities. Numerous studies on research and development, material application, production process improvements, and human physiological measurements for the sport shoe market exist. However, few studies have conducted an in-depth investigation on the design of forms and external appearance for sports shoes.     

A mobile dual-arm manipulation robot system for stocking and disposing of items in a convenience store by using universal vacuum grippers for grasping items

ABSTRACT

A mobile dual-arm robot with universal vacuum grippers (UVG) for performing stocking and disposing tasks was developed. The robot grasps items in the tasks by using UVGs whose surface adapts to the various shapes of the items. A selection algorithm that determines whether the robot should use one or both manipulators to arrange an item was also developed. A ‘reachable-grasp pose’ is defined as a pose in which the robot’s UVG can easily place an item with a target attitude if it grasps the item. By using the selection algorithm, the robot re-grasps the item by adopting the reachable-grasp pose if the two manipulators do not collide when one is in the current grasp pose and the other is in the reachable-grasp pose. The robot system won the third prize of the Future Convenience Store Challenge 2018. In experiments on stocking and disposing tasks, the robot system achieved success rates of 100% for the stocking task and 80% for the disposing task. We believe that the results of this study will help researchers to develop a robot system for not only the stocking and disposing tasks but also other tasks in convenience stores (like customer interaction).     

Novel hybrid optimization algorithm using PSO and MADS for the trajectory estimation of a four track wheel skid-steered mobile robot

Several optimization algorithms, such as the particle swarm optimization (PSO), genetic algorithm (GA), and ant colony optimization, have previously been applied in order to reliably obtain more accurate trajectory estimation for mobile robot. However, these optimization algorithms can get easily trapped in local optima when solving a complex system, which has many local optima and many input variables. This paper proposes a novel hybrid optimization algorithm-based tuning of the extended Kalman filter, which involves the PSO and mesh adaptive direct search algorithms, prior to operation. As demonstrated by our experimental results, the advantages of the novel hybrid optimization algorithm resolve the limitations of other algorithms in the trajectory estimation of a four track wheel skid-steered mobile robot (4-TW SSMR).