一种轮式倒立摆机器人设计

倒立摆是检验各种控制理论的理想模型,通过它可以判断各类控制算法的有效性和控制性能.为此,结合K60微控制器强大的运算能力和丰富的接口功能,设计了该轮式倒立摆机器人,可以通过它验证各种新型控制算法.硬件上介绍了与姿态控制相关的姿态检测系统和电机驱动单元.软件上介绍了根据系统数学模型设计的互补滤波器、姿态控制器、方向控制器和速度控制器.实验结果表明:该系统具有良好的鲁棒性和稳定性,可以准确地对控制算法的有效性和控制性能进行判断.     

Dynamic modeling and step-climbing analysis of a two-wheeled stair-climbing inverted pendulum robot

ABSTRACT

In this study, the control of a two-wheeled stair-climbing inverted pendulum robot and its climbing motion are analyzed and discussed. The robot adopts a state-feedback controller with a feed-forward constant to stabilize the body and achieve step-climbing motion. The control parameter is considered based on the dynamic model motion on a flat surface and the static model of motion on the step. For climbing stairs with a narrow step tread, a constant torque is applied to reduce the space required for recovering the body stability after climbing. The stability of the robot is numerically analyzed by analyzing the orbital stability of its limit cycle. The stability analysis shows that the control method can achieve a stable stair-climbing motion. The effectiveness of the control method is demonstrated through an experiment. The result indicates that the robot can climb the stairs, and the required time for climbing a single step is approximately 1.8?s.     

Characterization of motion power loss of off-road wheeled robot in a slippery terrain

For the first time in realm of power study of off-road wheeled robots, this study deals with motion power loss due to slippage of robot wheels traversed on slippery terrain. For this purpose, effects of slippery terrain type (solid balls with diameter of 0.0127, 0.0254, and 0.0508 m), tire air pressure (20.68, 34.47, and 55.16 kPa), and robot forward speed (0.17, 0.33, and 0.5 m/s) on the power loss were characterized. Derived results proved that the increasing effect of slippery terrain type on the power loss was dominant (1.08 and 3.21 times) than that of robot forward speed and tire air pressure, respectively. Meanwhile, the increasing effect of robot forward speed on the power loss was prevailed (2.98 times) than that of tire air pressure. Hence, to minimize the power loss of the robot traversed on each type of slippery terrain, adjustment of robot forward speed should be considered as first priority. A comparison between motion power loss (43.60–249.40 W) and provided motion power for the robot (136–436.37 W) implies that 12.93–75.44% of provided motion power was wasted by slippage of the robot wheels on slippery terrains. Overall, the analytical results obtained in this study lead to open a new prospection for comprehending of the power loss trends of off-road wheeled robots traversed on slippery terrains. As slippery terrain composed of solid balls, the results can be especially utilized for final phase of unloading robotic operations of catalyst handling procedure in process towers and reactors of oil, gas, petrochemical, and chemical industries.     

基于内部传感器的轮式移动机器人运动速度估计

讨论了在无速度传感器的情况下轮式移动机器人的速度估计问题, 采用了加速度传感器和位置传感器的输出实时估计轮式移动机器人速度, 并用一种按加速度扰动调整权值的方法融合来自不同传感器的数据. 实验验证了方法的有效性.     

Wheeled inverted pendulum type assistant robot: design concept and mobile control

This paper describes the design concept of the human assistant robot I-PENTAR (Inverted PENdulum Type Assistant Robot) aiming at the coexistence of safety and work capability and its mobile control strategy. I-PENTAR is a humanoid type robot which consists of a body with a waist joint, arms designed for safety, and a wheeled inverted pendulum mobile platform. Although the arms are designed low-power and lightweight for safety, it is able to perform tasks that require high power by utilizing its self-weight, which is the feature of a wheeled inverted pendulum mobile platform. I-PENTAR is modeled as a three dimensional robot; with controls of inclination angle, horizontal position, and steering angle to achieve high mobile capability. The motion equation is derived considering the non-holonomic constraint of the two-wheeled mobile robot, and a state feedback control method is applied for basic mobile controls wherein the control gain is calculated by the LQR method. Through several experiments of balancing, linear running, and steering, it was confirmed that the robot could realize stable mobile motion in a real environment by the proposed controller.     

轮式焊接机器人的设计

本文介绍了一种新型的基于电弧传感器的轮式焊接机器人,对其硬件组成,各部分功能及整体机构的控制方法作了阐述和分析,通过实验证明了这种机器人设计的有效性和合理性,最后对它的应用作了展望并提出了下一步改进的方向。     

Ultrasonic navigation for a wheeled nonholonomic vehicle

In this paper, we demonstrate a reliable and robust system for localization of mobile robots in indoors environments which are relatively consistent to a priori known maps. Through the use of an Extended Kalman Filter combining dead-reckoning, ultrasonic, and infrared sensor data, estimation of the position and orientation of the robot is achieved. Based on a thresholding approach, unexpected obstacles can be detected and their motion predicted. Experimental results from implementation on our mobile robot, Nomad-200, are also presented.     

Design of a multilink-articulated wheeled pipeline inspection robot using only passive elastic joints

This paper presents a multilink-articulated robot with omni and hemispherical wheels (AIRo-2.1) for inspecting and exploring pipelines. To quickly adapt to winding pipes, holonomic rolling movement without moving forward and backward is useful. However, this requires the rolling actuators to replace the driving actuators at the expense of the driving force. Furthermore, so far the number of driving wheels and torsion springs, magnitude of driving forces, stiffness and natural angle of the spring that are required to adapt to various pipelines have not been clarified. In this paper, we investigate the possibility of high maneuverability of multilink-articulated robots in winding pipes with as few driving actuators as possible and only elastic joints (torsion springs) for body bending. We further validate its effectiveness by experimental verification.     

Adaptive critic motion control design of autonomous wheeled mobile robot by dual heuristic programming

Autonomous wheeled mobile robot (WMR) needs implementing velocity and path tracking control subject to complex dynamical constraints. Conventionally, this control design is obtained by analysis and synthesis or by domain expert to build control rules. This paper presents an adaptive critic motion control design, which enables WMR to autonomously generate the control ability by learning through trials. The design consists of an adaptive critic velocity control loop and a self-learning posture control loop. The neural networks in the velocity neuro-controller (VNC) are corrected with the dual heuristic programming (DHP) adaptive critic method. Designer simply expresses the control objective by specifying the primary utility function then VNC will attempt to fulfill it through incremental optimization. The posture neuro-controller (PNC) learns by approximating the specialized inverse velocity model of WMR so as to map planned positions to suitable velocity commands. Supervised drive supplies variant velocity commands for PNC and VNC to set up their neural weights. During autonomous drive, while PNC halts learning VNC keeps on correcting its neural weights to optimize the control performance. The proposed design is evaluated on an experimental WMR. The results show that the DHP adaptive critic design is a useful base of autonomous control.     

Following control approach based on model predictive control for wheeled inverted pendulum robot

Personal robots, which are seen as tools that will be needed to support our aging society, will be expected to support the comfortable lifestyles of healthy young people as well as the elderly. However, excessive and premature robot support may adversely impact the physical abilities of their human owner/operators. In this paper, the authors propose a personal robot equipped with wheeled inverted pendulum control that can carry baggage and follow the human being. Since such robots could remove the drudgery associated with carrying luggage, their use could also encourage people to go outside and walk briskly, which could contribute to improved health management. This paper proposes a novel control approach for a robot following the human being. The proposed approach employs a model predictive control that facilitates consideration of several types of upper and lower level constraints a personal robot would require. The effectiveness of our proposed approach was then verified in experiments using a prototype personal robot.     

Design of a PID optimized neural networks and PD fuzzy logic controllers for a two‐wheeled mobile robot

In this paper, two intelligent techniques for a two‐wheeled differential mobile robot are designed and presented: A smart PID optimized neural networks based controller (SNNPIDC) and a PD fuzzy logic controller (PDFLC). Basically, mobile robots are required to work and navigate under exigent circumstances where the environment is hostile, full of disturbances such as holes and stones. The robot navigation leads to an autonomous decision making to overcome an obstacle and/or to stop the engine to protect it. In fact, the actuators that drive the robot should in no way be damaged and should stop to change direction in case of insurmountable disturbances. In this context, two controllers are implemented and a comparative study is carried out to demonstrate the effectiveness of the proposed approaches. For the first one, neural networks are used to optimize the parameters of a PID controller and for the second a fuzzy inference system type Mamdani based controller is adopted. The goal is to implement control algorithms for safe robot navigation while avoiding damage to the motors. In these two control cases, the smart robot has to quickly perform tasks and adapt to changing environment conditions while ensuring stability and accuracy and must be autonomous with regards to decision making. Simulations results aren't done in real environments, but are obtained with the Matlab/Simulink environment in which holes and stones are modeled by different load torques and are applied as disturbances on the mobile robot environment. These simulation results and the robot performances are satisfactory and are compared to a PID controller in which parameters are tuned by the Ziegler–Nichols tuning method. The applied methods have proven to be highly robust.     

Control of an articulated wheeled mobile robot in pipes

We propose a control method in which an articulated wheeled mobile robot moves inside straight, curved and branched pipes. This control method allows the articulated wheeled mobile robot to inspect a larger area. The articulated wheeled mobile robot comprises pitch and yaw joints is and propelled by active wheels attached to the robot. Via the proposed control method, the robot takes on two different shapes; one prevents the robot from slipping inside straight pipes and the other allows movement in a pipe that curves in any direction. The robot is controlled by a simplified model for the robot's joint angles. The joint angles of the robot are obtained by fitting to a continuous curve along the pipe path. In addition, the angular velocity of the robot's active wheels is determined by a simplified model. The effectiveness of the proposed the control method was demonstrated with a physical implementation of the robot, and the robot was able to move inside straight, curved and branched pipes.     

Classification of reflectors with an ultrasonic sensor for mobile robot applications

This paper describes a sensor model made up of four ultrasonic transducers able to classify reflectors (wall, edge or corner) in specular environments. The main goal has been to effect the classification from a single reading cycle: emission of ultrasounds and reception of echoes (measuring only times of flight—TOFs). Working from the four TOFs obtained after a single emission of ultrasounds (thereby facilitating its practical implementation in a mobile robot, when readings are taken while the robot is moving), an algorithm has been proposed for discriminating between edge and plane type reflectors. The configuration of the four transducers enabled dependent discriminating functions to be determined directly from the quadratic terms of the TOFs, without the need for previous geometric transformations. Special attention was given to the effect of the separation between the sensor transducers and the reading-associated noise. Finally, some considerations have been pointed out about the possibility of two transducers emitting, so allowing discrimination between walls and corners.     

机器人触须传感器的设计

提出了一种利用触须来识别物体表面轮廓的新方法。传感器采用了二维PSD作为敏感元件,实时地测量由于与物体接触在触须根部所产生的微小位移量。介绍了机器人触须传感器具体的结构及工作原理。由实验数据可知,触须根部位移量的大小与接触的距离成反比,且距离越近位移量变化的速度越快。由此可获得待测物体的位置、距离、角度等信息。     

Feature extraction method for a robot map using neural networks

Many map-building algorithms using ultrasonic sensors have been developed for mobile robot applications. In indoor environments, the ultrasonic sensor system gives some uncertain data. To compensate for this effect, a new feature extraction method using neural networks is proposed. A new, effective representation of the target is defined, and the reflection wave data patterns are learnt using neural networks. As a consequence, the targets are classified as planes, corners, or edges, which all frequently occur in indoor environments. We constructed our own robot system for the experiments which were carried out to show the performance. This work was presented in part at the 7th International Symposium on Artificial Life and Robotics, Oita, Japan, January 16–18, 2002     

基于行为的轮式移动机器人导航控制

介绍了一种轮式移动机器人CASIA-I及其运动机构,针对该运动机构给出了机器人的运动方程和基于行为的导航控制算法,并根据该算法进行了软件仿真和实物实验．实验结果表明,该导航控制算法是一种有效的导航算法．     

Development of a single-wheeled inverted pendulum robot capable of climbing stairs

ABSTRACT

In this paper, we propose the design of a single-wheeled robot capable of climbing stairs. The robot is equipped with the proposed climbing mechanism, which enables it to climb stairs. The mechanism has an extremely simple structure, comprised of a parallel arm, belt, harmonic drive, and pulley. The proposed climbing mechanism has the advantage of not requiring an additional actuator because it can be driven by using a single actuator that drives the wheel. The robot is equipped with a control moment gyroscope to control the stability in a lateral direction. Experimental results demonstrate that the robot can climb stairs with a riser height of 12–13?cm and a tread depth of 39?cm at an approximate rate of 2 to 3 s for each step.     

Double-track mobile robot for hazardous environment applications

This paper introduces a link-type tracked vehicle, which is developed for potential applications such as fire fighting, handicapped assistance and mine detection in various hazardous environments. The vehicle consists of three parts—front frame, rear frame and body. The front frame is connected to the rear frame by a rotational passive adaptation mechanism, which is the driving mechanism of the vehicle. This is similar to a link structure such that one frame rotates to the other by external forces between the vehicle and the ground. This passive adaptation mechanism permits good adaptability to uneven terrain including stairs. This link structure also improves energy efficiency, and makes the vehicle simple and small. The body is a control system for remote control of the vehicle. It communicates visual and distance information to the operator, and commands direction and velocity orders.     

Mobile robot localization based on effective combination of vision and range sensors

Most localization algorithms are either range-based or vision-based, but the use of only one type of sensor cannot often ensure successful localization. This paper proposes a particle filter-based localization method that combines the range information obtained from a low-cost IR scanner with the SIFT-based visual information obtained from a monocular camera to robustly estimate the robot pose. The rough estimation of the robot pose by the range sensor can be compensated by the visual information given by the camera and the slow visual object recognition can be overcome by the frequent updates of the range information. Although the bandwidths of the two sensors are different, they can be synchronized by using the encoder information of the mobile robot. Therefore, all data from both sensors are used to estimate the robot pose without time delay and the samples used for estimating the robot pose converge faster than those from either range-based or vision-based localization. This paper also suggests a method for evaluating the state of localization based on the normalized probability of a vision sensor model. Various experiments show that the proposed algorithm can reliably estimate the robot pose in various indoor environments and can recover the robot pose upon incorrect localization. Recommended by Editorial Board member Sooyong Lee under the direction of Editor Hyun Seok Yang. This research was conducted by the Intelligent Robotics Development Program, one of the 21st Century Frontier R&D Programs funded by the Ministry of Knowledge Economy of Korea. Yong-Ju Lee received the B.S. degree in Mechanical Engineering from Korea University in 2004. He is now a Student for Ph.D. of Mechanical Engineering from Korea University. His research interests include mobile robotics. Byung-Doo Yim received the B.S. degree in Control and Instrumentation Engineering from Seoul National University of Technology in 2005. Also, he received the M.S. degree in Mechatroncis Engineering from Korea University in 2007. His research interests include mobile robotics. Jae-Bok Song received the B.S. and M.S. degrees in Mechanical Engineering from Seoul National University in 1983 and 1985, respectively. Also, he received the Ph.D. degree in Mechanical Engineering from MIT in 1992. He is currently a Professor of Mechanical Engineering, Korea University, where he is also the Director of the Intelligent Robotics Laboratory from 1993. His current research interests lie mainly in mobile robotics, safe robot arms, and design/control of intelligent robotic systems.     

Modeling,analysis and compensation of disturbances during task execution of a wheeled inverted pendulum type assistant robot using a unified controller

This paper presents the modeling and analysis of disturbances caused by model changes, unknown dynamics, and external forces during task execution of a wheeled Inverted PENdulum Type Assistant Robot. Compensating these disturbances and their effects results in the ability of the system to perform different tasks without changes in the control structure. This results in a unified controller for multiple tasks making the control system simple without sacrificing robustness. Estimation of these disturbances is performed using the extended state observer (ESO), which is a practical observer since it requires very little system information. To ensure proper application of the ESO, the analysis of the equilibrium states under disturbances was performed. The disturbance modeling and the effectiveness of the control are verified by results from disturbance and task tests. Finally, the bounded input bounded output behavior of the system with consideration to the disturbances is presented.