Development of a stair-climbing mobile robot with legs and wheels

This paper deals with the development of a stair-climbing mobile robot with legs and wheels. The main technical issues in developing this type of robot are the stability and speed of the robot while climbing stairs. The robot has two wheels in the front of the body to support its weight when it moves on flat terrain, and it also has arms between the wheels to hook onto the tread of stairs. There are two pairs of legs in the rear of the body. Using not only the rorational torque of the arms and the wheels, but also the force of the legs, the robot goes up and down stairs. It measures the size of stairs when going up and down the first step, and therefore the measurement process does not cause this robot to lose any time. The computer which controls the motion of the robot needs no complicated calculations as other legged robots do. The mechanism of this robot and the control algorithm are described in this paper. This robot will be developed as a wheelchair with a stair climbing mechanism for disabled and elderly people in the near future. This work was presented, in part, at the International Symposium on Artificial Life and Robotics, Oita, Japan, February 18–20, 1996     

Optimal design of a stair-climbing mobile robot with flip mechanism

Stairs overcoming is a primary challenge for mobile robots moving in human environments, and the contradiction between the portability and the adaptability of stair climbing robot is not well resolved. In this paper, we present an optimal design of a flip-type mobile robot in order to improve the adaptability as well as stability while climbing stairs. The kinematic constraints on the flip mechanism are derived to prevent undesired interferences among stairs, wheels and main body during climbing stairs. The objective function is proposed according to the traction demand of the robot during stair-climbing motion for the first time and the value of the objective function is calculated though kinetic analysis. The Taguchi method is using as the optimization tool because of its simplicity and cost-effectiveness both in formulating an objective function and in satisfying multiple constraints simultaneously. The performance of the robot under the optimal parameters is verified through simulations and experiments.     

Real-time panospheric image dewarping and presentation for remote mobile robot control

The panospheric camera used by novice drivers in the United States to navigate the Nomad robot across a desert in Chile provides an omnidirectional, ground-to-sky view of the remote robot's environment. This paper describes the texture mapping techniques used to continuously dewarp and display the image for tele-explorers in Pittsburgh, PA and Mountain View, CA.     

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.     

Fuzzy logic techniques for mobile robot obstacle avoidance

This paper is concerned with the problem of reactive navigation for a mobile robot in an unknown clustered environment. We will define reactive navigation as a mapping between sensory data and commands. Building a reactive navigation system means providing such a mapping. It can come from a family of predefined functions (like potential fields methods) or it can be built using ‘universal’ approximators (like neural networks). In this paper, we will consider another ‘universal’ approximator: fuzzy logic. We will explain how to choose the rules using a behaviour decomposition approach. It is possible to build a controller working quite well but the classical problems are still there: oscillations and local minima. Finally, we will conclude that learning is necessary for a robust navigation system and fuzzy logic is an easy way to put some initial knowledge in the system to avoid learning from zero.     

A bacterial colony growth algorithm for mobile robot localization

Achieving robot autonomy is a fundamental objective in Mobile Robotics. However in order to realize this goal, a robot must be aware of its location within an environment. Therefore, the localization problem (i.e.,the problem of determining robot pose relative to a map of its environment) must be addressed. This paper proposes a new biology-inspired approach to this problem. It takes advantage of models of species reproduction to provide a suitable framework for maintaining the multi-hypothesis. In addition, various strategies to track robot pose are proposed and investigated through statistical comparisons. The Bacterial Colony Growth Algorithm (BCGA) provides two different levels of modeling: a background level that carries on the multi-hypothesis and a foreground level that identifies the best hypotheses according to an exchangeable strategy. Experiments, carried out on the robot ATRV-Jr manufactured by iRobot, show the effectiveness of the proposed BCGA.

Implementing distributed control system for intelligent mobile robot

The control system of a mobile robot has a number of issues to deal with in real time, including motion control, mapping, localization, path planning, and sensor processing. Intelligent reasoning, task-oriented behaviors, human–robot interfaces, and communications add more tasks to be solved. This naturally leads to a complex hierarchical control system where various tasks have to be processed concurrently. Many low-level tasks can be handled by a robots onboard (host) computer. However, other tasks, such as speech recognition or vision processing, are too computationally intensive for one computer to process. In this case, it is better to consider a distributed design for the control system in networked environments. In order to achieve maximum use of the distributed environment, it is important to design and implement the distributed system and its communication mechanisms in an effective and flexible way. This article describes our approach to designing and implementing a distributed control system for an intelligent mobile robot. We present our implementation of such a distributed control system for a prototype mobile robot. We focus our discussion on the system architecture, distributed communication mechanisms, and distributed robot control.This work was presented, in part, at the 8th International Symposium on Artificial Life and Robotics, Oita, Japan, January 24–26, 2003     

Reliable people tracking approach for mobile robot in indoor environments

There is a great challenge that a mobile robot reliably and continuously tracks a specific person in indoor environments. In this paper, a novel method is presented, which can effectively recognize and reliably track a target person based on mobile robot vision. Gabor wavelet and hidden Markov model (HMM) are firstly employed for identifying the target person. In order to effectively track the specific person and reduce the computational cost in tracking stage, horizontal-projecting probability histogram (HPPH) of upper body color clothes region is proposed for extracting the pattern features, which significantly improves the tracking reliability and, at the same time, unscented particle filter (UPF) is integrated and PID operator is introduced for controlling the robot to follow the person. Experimental results validate the robustness and the reliability of this approach.     

基于环境势场的移动机器人主动定位

提出一种以环境势场提供辅助线索的主动定位方法.首先建立以环境中各标志物为场源的势场模型;然后为机器人构造以窗口势函数极大值位置和环境势函数极大值位置为主体的运动目标候选集合,并以行为效用和行为代价构成评价函数,从中选出目标位置, 进而确定运动方向;最后根据机器人的运动能力和评价函数分别确定下一步的位移和观测方向.仿真结果验证了该方法的有效性.     

部分未知环境中移动机器人动态路径规划方法

针对部分未知环境,提出一种基于粒子滤波的动态路径规划方法.将全局最优路径视为受机器人运动及环境影响的变化量,采用粒子滤波算法,利用机器人运动信息预测路径,并利用实时环境信息更新路径,通过在线跟踪全局最优路径获得不断更新的全局优化路径.将传统全局路径规划先规划后执行的模式改为边规划边执行的模式,既减少了等待时间,又为机器人的移动误差及部分未知环境提供了较强的适应能力.仿真及实验验证,该方法的有效性.     

A user study of command strategies for mobile robot teleoperation

This article presents a user study of mobile robot teleoperation. Performance of speed, position and combined command strategies in combination with text, visual and haptic feedback information were evaluated by experiments. Two experimental tasks were designed as follows: positioning of mobile robot and navigation in complex environment. Time for task completion and motion accuracy were measured and compared for different command strategies and types of feedback. Role of haptic, text and visual feedback information in combination with described command strategies is outlined.     

Optimal patrolling methodology of mobile robot for unknown visitors

This paper focuses on patrolling missions for monitoring visitors in an environment. A single mobile robot is used. For the robot, it is required to monitor as many visitors as possible utilizing the mobility and monitoring capabilities. A challenge in the patrolling missions is that the robot does not have information about the visitors beforehand. For the unknown visitors, the robot is required to identify the trends. For this purpose, a Bayesian learning approach is applied to this robot. The identified visitor trends allow the robot to employ patrolling strategies. This is the adaptability of the patrolling robot to the unknown visitors. In this paper, we present an optimal patrolling strategy based on a value iteration method. The robot is enabled to have an optimal policy that suggests three patrolling decisions, such as the target monitoring area, monitoring time, and patrolling path in an integrated way. Furthermore, the optimal patrolling strategy is improved from the viewpoint of exploration and exploitation of information about the unknown visitors in the environment. Through simulation experiments, we discuss the effectiveness of the patrolling strategy.     

Design of a gravitational wheeled robot

This paper deals with a novel mobile robot to overcome unusual sized obstacles or uneven ground. The robot proposed here has a compact driving mechanism between dual parallel big wheels. First, we explain the basic principle and structure of our robot, and show the specifications of our prototype robot and the result of some mechanical experiments. In these experiments, we also report the result of the velocity control accompanied with two one-chip microcomputers (PICs) and we design a new leg for the attachment of a range sensor. Finally, we summarize our obtained results and some future works.     

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.

Lyapunov function-based obstacle avoidance scheme for a two-wheeled mobile robot

An obstacle avoidance scheme of a two-wheeled mobile robot is shown by selecting an appropriate Lya- punov function. When considering the obstacle, the Lyapunov function may have some local minima. A method which erases the local minima is proposed by using a function which covers the minima with a plane surface. The effectiveness of the proposed method is verified by numerical simulations.     

基于灰色定性理论的移动机器人地图创建

针对移动机器人自主导航地图创建中超声波信息存在不确定性的问题,提出一种新的基于灰色定性理论的超声波信息解释和融合的方法,并用于处理超声波传感器信息和移动机器人创建环境地图．首先,引入概率灰数对超声波信息的不确定性进行描述,以获得栅格单元和传感器的概率灰数模型;然后,设计超声波传感器新旧信息的融合方法,从而得到环境地图的整体表示;最后通过地图创建仿真实验结果表明了这种方法具有良好的鲁棒性和准确度．     

多障碍环境中移动机器人的光滑轨迹规划

根据轮式移动机器人参数化轨迹生成模型,结合多障碍物结构化环境中障碍物的建模,把其和参数化轨迹规划模型融合,得到了具有一般性的多障碍物环境中轮式移动机器人光滑轨迹规划模型;并利用最优化控制原理,建立了任意性能指标下,多障碍物环境中最优参数化轨迹生成模型。结合数值求解方法,推导了多障碍物环境中参数化轨迹规划非线性求解模型的求解方法。最后通过仿真验证了参数化轨迹规划求解模型的正确性。     

一种动态未知环境下的机器人路径搜索方法

提出了一种新的路径搜索算法——"触觉感知法"来实现机器人在未知静态与动态环境情况下的路径搜索。该方法不需要提供地图信息,机器人仅收集目标点的距离和方位信息以及通过自带传感器作为触觉器收集周围局部环境信息。机器人以BP神经网络作为决策器,经过训练,可以在静态和动态环境中搜索出一条光滑无碰撞且便捷并能有效避开动态障碍物的运动轨迹。对所提出的方法进行了仿真实验,仿真结果表明算法在静态和动态环境下均能有高效率的路径搜索表现。     

基于移动机器人路径规划的鼠群算法

研究静态环境下机器人路径规划问题,并根据老鼠觅食行为提出一种鼠群算法.该算法引入环境因子和经验因子,每次搜索后对路径进行经验因子更新,通过迭代的方式寻找静态环境下机器人最佳路径.同时提出一种禁忌策略,有效地避免了路径死锁问题.理论分析和实验结果表明,该算法能使机器人在有较多障碍的环境下迅速找到一条优化路径,而且安全避碰,与同类算法相比具有一定的优越性.     

A novel efficient algorithm for mobile robot localization

Being autonomous is one of the most important goals in mobile robots. One of the fundamental works to achieve this goal is giving the ability to a robot for finding its own correct position and orientation. Different methods have been introduced to solve this problem. In this paper, a novel method based on the harmony search (HS) algorithm for robot localization through scan matching is proposed. Simulation results show that the proposed method in comparison with a genetic algorithm-based approach has better accuracy and higher performance. Furthermore a new hybrid algorithm based on harmony search and differential evolution (DE) algorithms is proposed and evaluated on different benchmark functions. Finally the hybrid algorithm has been applied for mobile robot localization and it outperformed the HS-based approach.