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Obstacle avoidance technology of bionic quadruped robot based on multi-sensor information fusion
Obstacle avoidance technology of bionic quadruped robot based on multi-sensor information fusion
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韩宝玲,张天,罗庆生,朱颖,宋明辉
- , 2016, DOI: 10.15918/j.jbit1004-0579.201625.0402
Abstract: In order to improve the ability of a bionic quadruped robot to percept the location of obstacles in a complex and dynamic environment, the information fusion between an ultrasonic sensor and a binocular sensor was studied under the condition that the robot moves in the Walk gait on a structured road. Firstly, the distance information of obstacles from these two sensors was separately processed by the Kalman filter algorithm, which largely reduced the noise interference. After that, we obtained two groups of estimated distance values from the robot to the obstacle and a variance of the estimation value. Additionally, a fusion of the estimation values and the variances was achieved based on the STF fusion algorithm. Finally, a simulation was performed to show that the curve of a real value was tracked well by that of the estimation value, which attributes to the effectiveness of the Kalman filter algorithm. In contrast to statistics before fusion, the fusion variance of the estimation value was sharply decreased. The precision of the position information is 4.6.cm, which meets the application requirements of the robot.
In order to improve the ability of a bionic quadruped robot to percept the location of obstacles in a complex and dynamic environment, the information fusion between an ultrasonic sensor and a binocular sensor was studied under the condition that the robot moves in the Walk gait on a structured road. Firstly, the distance information of obstacles from these two sensors was separately processed by the Kalman filter algorithm, which largely reduced the noise interference. After that, we obtained two groups of estimated distance values from the robot to the obstacle and a variance of the estimation value. Additionally, a fusion of the estimation values and the variances was achieved based on the STF fusion algorithm. Finally, a simulation was performed to show that the curve of a real value was tracked well by that of the estimation value, which attributes to the effectiveness of the Kalman filter algorithm. In contrast to statistics before fusion, the fusion variance of the estimation value was sharply decreased. The precision of the position information is 4.6.cm, which meets the application requirements of the robot.
Behavior Selection Based Navigation and Obstacle Avoidance Approach Using Visual and Ultrasonic Sensory Information for Quadruped Robots
Kiyotaka Izumi,Maki K. Habib,Keigo Watanabe,Ryoichi Sato
International Journal of Advanced Robotic Systems , 2008,
Abstract: A robot functioning in an environment may exhibit various forms of behavior emerge from the interaction with its environment through sense, control and plan activities. Hence, this paper introduces a behaviour selection based navigation and obstacle avoidance algorithm with effective method for adapting robotic behavior according to the environment conditions and the navigated terrain. The developed algorithm enable the robot to select the suitable behavior in real-time to avoid obstacles based on sensory information through visual and ultrasonic sensors utilizing the robot's ability to step over obstacles, and move between surfaces of different heights. In addition, it allows the robot to react in appropriate manner to the changing conditions either by finetuning of behaviors or by selecting different set of behaviors to increase the efficiency of the robot over time. The presented approach has been demonstrated on quadruped robot in several different experimental environments and the paper provides an analysis of its performance.
Control Strategies for Mobile Robot With Obstacle Avoidance  [PDF]
M. Zohaib,M. Pasha,R. A. Riaz,N. Javaid,M. Ilahi,R. D. Khan
Computer Science , 2013,
Abstract: Obstacle avoidance is an important task in the field of robotics, since the goal of autonomous robot is to reach the destination without collision. Several algorithms have been proposed for obstacle avoidance, having drawbacks and benefits. In this survey paper, we mainly discussed different algorithms for robot navigation with obstacle avoidance. We also compared all provided algorithms and mentioned their characteristics; advantages and disadvantages, so that we can select final efficient algorithm by fusing discussed algorithms. Comparison table is provided for justifying the area of interest
Applying Evolutionary Optimisation to Robot Obstacle Avoidance  [PDF]
Olivier Pauplin,Jean Louchet,Evelyne Lutton,Michel Parent
Computer Science , 2005,
Abstract: This paper presents an artificial evolutionbased method for stereo image analysis and its application to real-time obstacle detection and avoidance for a mobile robot. It uses the Parisian approach, which consists here in splitting the representation of the robot's environment into a large number of simple primitives, the "flies", which are evolved following a biologically inspired scheme and give a fast, low-cost solution to the obstacle detection problem in mobile robotics.
Optical Flow based Robot Obstacle Avoidance
Kahlouche Souhila,Achour Karim
International Journal of Advanced Robotic Systems , 2008,
Abstract: In this paper we try to develop an algorithm for visual obstacle avoidance of autonomous mobile robot. The input of the algorithm is an image sequence grabbed by an embedded camera on the B21r robot in motion. Then, the optical flow information is extracted from the image sequence in order to be used in the navigation algorithm. The optical flow provides very important information about the robot environment, like: the obstacles disposition, the robot heading, the time to collision and the depth. The strategy consists in balancing the amount of left and right side flow to avoid obstacles, this technique allows robot navigation without any collision with obstacles. The robustness of the algorithm will be showed by some examples.
Dynamic Obstacle Avoidance for an Omnidirectional Mobile Robot  [PDF]
Robert L. Williams II,Jianhua Wu
Journal of Robotics , 2010, DOI: 10.1155/2010/901365
Abstract: We have established a novel method of obstacle-avoidance motion planning for mobile robots in dynamic environments, wherein the obstacles are moving with general velocities and accelerations, and their motion profiles are not preknown. A hybrid system is presented in which a global deliberate approach is applied to determine the motion in the desired path line (DPL), and a local reactive approach is used for moving obstacle avoidance. A machine vision system is required to sense obstacle motion. Through theoretical analysis, simulation, and experimental validation applied to the Ohio University RoboCup robot, we show the method is effective to avoid collisions with moving obstacles in a dynamic environment. 1. Introduction An omnidirectional robot is a holonomic robot that can move simultaneously in rotation and translation [1]. Most work on omnidirectional robots is in robot development; the few studies on dynamic models are Watanabe et al. [2], Moore and Flann [3], Williams et al. [4], and Kalmar-Nagy et al. [5]. These models all have decoupling between the wheels, which is not complete; thus, we first briefly summarize a new coupled nonlinear dynamics model for three-wheeled omnidirectional robots. The potential field method was first suggested by Andrews and Hogan [6] and Khatib [7] for obstacle avoidance of manipulators and mobile robots. Obstacles exert a virtual repulsive force, while the goal applies a virtual attractive force to the robot. Koren and Borenstein [8] identify potential field limitations (robot trapped by local minima, oscillation in presence of obstacle, and the lack of passage between closely spaced obstacles). To overcome these problems, they developed the vector field histogram. Ge and Cui [9] mentioned an additional shortcoming, a nonreachable goal with an obstacle nearby, and presented a new repulsive function to overcome it, increasing complexity and computation. Adams [10] presented a simulation study using the potential field method considering low-level robot dynamics, with static obstacles. Guldner and Utkin [11] proposed a method that took the gradient of the potential field as the desired vector field for path planning. Tsourveloudis et al. [12] proposed an electrostatic potential field for an autonomous mobile robot in a planar dynamic environment; their method depends on obstacle prediction accuracy and slow environment changes. The velocity space method to deal with moving obstacle avoidance in a preknown environment was suggested by Fiorini and Shiller [13], who discussed the velocity obstacle concept. This method
Obstacle Avoidance in Groping Locomotion of a Humanoid Robot
Hanafiah Yussof,Mitsuhiro Yamano,Yasuo Nasu,Kazuhisa Mitobe
International Journal of Advanced Robotic Systems , 2008,
Abstract: This paper describes the development of an autonomous obstacle-avoidance method that operates in conjunction with groping locomotion on the humanoid robot Bonten-Maru II. Present studies on groping locomotion consist of basic research in which humanoid robot recognizes its surroundings by touching and groping with its arm on the flat surface of a wall. The robot responds to the surroundings by performing corrections to its orientation and locomotion direction. During groping locomotion, however, the existence of obstacles within the correction area creates the possibility of collisions. The objective of this paper is to develop an autonomous method to avoid obstacles in the correction area by applying suitable algorithms to the humanoid robot's control system. In order to recognize its surroundings, six-axis force sensors were attached to both robotic arms as end effectors for force control. The proposed algorithm refers to the rotation angle of the humanoid robot's leg joints due to trajectory generation. The algorithm relates to the groping locomotion via the measured groping angle and motions of arms. Using Bonten-Maru II, groping experiments were conducted on a wall's surface to obtain wall orientation data. By employing these data, the humanoid robot performed the proposed method autonomously to avoid an obstacle present in the correction area. Results indicate that the humanoid robot can recognize the existence of an obstacle and avoid it by generating suitable trajectories in its legs.
Obstacle Avoidance of mobile robot using PSO based Neuro Fuzzy Technique
Sourav Dutta
International Journal on Computer Science and Engineering , 2010,
Abstract: Navigation and obstacle avoidance are veryimportant issues for the successful use of an autonomous mobilerobot. To allow the robot to move between its current and finalconfigurations without any collision within the surroundingenvironment, motion planning needs much treatment. Thus togenerate collision free path it should have proper motionplanning as well as obstacle avoidance scheme. This work mainlydeals with the obstacle avoidance of a wheeled mobile robot instructured environment by using PSO based neuro-fuzzyapproach. Here three layer neural network with PSO is used aslearning algorithm to determine the optimal collision-free path.
A New Approach for Mobile Robot Obstacle Avoidance Based on Multi-Sonar Information
一种基于多组传感器信息移动机器人的避障方法

Zhang Minglu,Peng Shangxian,
张明路
,彭商贤

自动化学报 , 1998,
Abstract: This paper presents a new approach for mobile robot to avoid obstacles based on multi-sonar information in an unknown environment. The approach takes multi-sonar information as the ART-2 neural network's inputs and quickly achieves identification and classification for the currently perceptual environment. Then, a fuzzy controller for mobile robot obstacle avoidance in an unknown environment is designed. In order to demonstrate the effectiveness and real-time ability of the proposed approach, we report a number of experimental results of mobile robot obstacle avoidance in an unknown environment.
基于生物反射模型的四足机器人坡面运动控制与越障研究
Study on quadruped robot ramp-trotting and obstacle-crossing based on biological reflex model
 [PDF]

葛卓,罗庆生,贾燕,李华师
- , 2017, DOI: 10.3969/j.issn.1001-0505.2017.04.012
Abstract: 为了提高四足机器人在包含坡面和障碍物等复杂地形中的运动能力与环境自适应能力,在对四足机器人基本步态研究的基础上,利用生物节律运动和反射控制机理,对四足机器人的适应性行走控制模型进行了研究.建立了适用于四足机器人坡面运动以及越障运动的前庭反射和屈肌反射数学模型,根据该数学模型构建的生物反射控制器与机器人膝、髋关节CPG控制网络有机融合,构成了协调性好、整体性高的控制系统.通过Adams/Matlab联合仿真,验证了所提出控制模型的可行性与有效性.该模型能够有效地使前膝后肘式四足机器人流畅、平稳地完成上下坡运动,并具备自适应越障运动能力.
To improve the locomotion ability and terrain adaptive ability of a quadruped robot through complex terrains including ramps and obstacles, based on the study of quadruped robot basic gaits, a biomimetic adaptive control model for the quadruped robot is studied with the mechanisms regarding animals’ rhythmic locomotion and reflex control. The mathematical models of vestibular and flexor reflexes are established to realize trotting on a ramp and obstacle crossing. Reflex controllers derived from the aforementioned mathematical models are integrated with the central pattern generator(CPG)networks of knee and hip joints of the robot, so that a control system is created with good coordination and high degree of integrity. By co-simulation of Adams and Matlab, the feasibility and effectiveness of both the vestibular reflex model and the flexor reflex model are verified. Under the control of such control model, the quadruped robot with all outward knee joints can stably trot uphill or downhill and adaptively achieve obstacle avoidance and crossing
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