Method for Detecting Moving Obstacles Using Passive 3D Visual Sensor

1993 ◽  
Vol 5 (4) ◽  
pp. 388-400
Author(s):  
Jun'ichi Takeno ◽  
◽  
Naoto Mizuguchi ◽  
Sakae Nishiyama ◽  
Kanehiro Sorimachi ◽  
...  
Keyword(s):  
Visual System ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Real Time ◽  
Visual Sensor ◽  
Real Time Processing ◽  
Moving Obstacles ◽  
The Right ◽  
Moving Obstacle ◽  
Auto Focusing

Of primary importance for mobile robots is their smooth movement to the targeted destination. To achieve this purpose, mobile robots must be able to detect a person in their environment, another mobile robot, or an object not described in the map and to avoid collision with it. Recognizing the strong need for providing robots with a visual system to evade obstacles, the authors first developed a real-time visual system to detect a moving obstacle and then studied the possibility of avoiding collisions by mounting the system on a mobile robot. The visual sensor used in this system is a passive optical stereo without any mechanical moving parts. Using a special slit patten, the sensor is configured in order to split the two images obtained by individual cameras place on the right and left and to project the split images onto one CCD sensor, providing approximately 200 auto-focusing subsystems. The sub-systems can operate independently of one another, enabling real-time processing. This paper reports on a visual sensor, a solution to the measurement accuracy problem concerning the detection of moving obstacles using the sensor, and visual system experiments on real-time detection of an actually moving object using the sensor.

Navigation of mobile robots with collision avoidance for moving obstacles

2005 ◽  
Vol 219 (1) ◽  
pp. 99-110 ◽  
Author(s):  
A Fujimori
Keyword(s):  
Numerical Simulation ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Collision Avoidance ◽  
Avoidance Behaviour ◽  
Infrared Sensor ◽  
Moving Obstacles ◽  
Unknown Environments ◽  
Moving Obstacle

This paper presents a collision avoidance technique of mobile robots for moving obstacles in unknown environments. The mobile robot considered in this paper has a sensor measuring the distance between the robot and a moving obstacle, such as an ultrasonic sonar or infrared sensor. Avoidance behaviour for moving obstacles is proposed. The collision avoidance conditions for two typical aspects under which the robot encounters a moving obstacle are derived and are used as guidelines for designing the navigation parameters. The effectiveness of the proposed technique is demonstrated by numerical simulation examples.

Navigation of a wheeled mobile robotic agent using modified grey wolf optimization controller

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chittaranjan Paital ◽  
Saroj Kumar ◽  
Manoj Kumar Muni ◽  
Dayal R. Parhi ◽  
Prasant Ranjan Dhal
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Real Time ◽  
Autonomous Navigation ◽  
Simulation Software ◽  
Grey Wolf ◽  
Grey Wolf Optimization ◽  
Content Type ◽  
Cluttered Environment

PurposeSmooth and autonomous navigation of mobile robot in a cluttered environment is the main purpose of proposed technique. That includes localization and path planning of mobile robot. These are important aspects of the mobile robot during autonomous navigation in any workspace. Navigation of mobile robots includes reaching the target from the start point by avoiding obstacles in a static or dynamic environment. Several techniques have already been proposed by the researchers concerning navigational problems of the mobile robot still no one confirms the navigating path is optimal.Design/methodology/approachTherefore, the modified grey wolf optimization (GWO) controller is designed for autonomous navigation, which is one of the intelligent techniques for autonomous navigation of wheeled mobile robot (WMR). GWO is a nature-inspired algorithm, which mainly mimics the social hierarchy and hunting behavior of wolf in nature. It is modified to define the optimal positions and better control over the robot. The motion from the source to target in the highly cluttered environment by negotiating obstacles. The controller is authenticated by the approach of V-REP simulation software platform coupled with real-time experiment in the laboratory by using Khepera-III robot.FindingsDuring experiments, it is observed that the proposed technique is much efficient in motion control and path planning as the robot reaches its target position without any collision during its movement. Further the simulation through V-REP and real-time experimental results are recorded and compared against each corresponding results, and it can be seen that the results have good agreement as the deviation in the results is approximately 5% which is an acceptable range of deviation in motion planning. Both the results such as path length and time taken to reach the target is recorded and shown in respective tables.Originality/valueAfter literature survey, it may be said that most of the approach is implemented on either mathematical convergence or in mobile robot, but real-time experimental authentication is not obtained. With a lack of clear evidence regarding use of MGWO (modified grey wolf optimization) controller for navigation of mobile robots in both the environment, such as in simulation platform and real-time experimental platforms, this work would serve as a guiding link for use of similar approaches in other forms of robots.

Special Issue on Mobile Robot

1999 ◽  
Vol 11 (1) ◽  
pp. 1-1
Author(s):  
Kiyoshi Komoriya ◽  
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Autonomous Navigation ◽  
High Speed ◽  
Outdoor Environment ◽  
Special Issue ◽  
Visual Sensor ◽  
Planning Stage ◽  
International Conference ◽  
Position Detection

Mobility, or locomotion, is as important a function for robots as manipulation. A robot can enlarge its work space by locomotion. It can also recognize its environment well with its sensors by moving around and by observing its surroundings from various directions. Much researches has been done on mobile robots and the research appears to be mature. Research activity on robot mobility is still very active; for example, 22% of the sessions at ICRA'98 - the International Conference on Robotics and Automation - and 24% of the sessions at IROS'98 - the International Conference on Intelligent Robots and Systems - dealt with issues directly related to mobile robots. One of the main reasons may be that intelligent mobile robots are thought to be the closest position to autonomous robot applications. This special issue focuses on a variety of mobile robot research from mobile mechanisms, localization, and navigation to remote control through networks. The first paper, entitled ""Control of an Omnidirectional Vehicle with Multiple Modular Steerable Drive Wheels,"" by M. Hashimoto et al., deals with locomotion mechanisms. They propose an omnidirectional mobile mechanism consisting of modular steerable drive wheels. The omnidirectional function of mobile mechanisms will be an important part of the human-friendly robot in the near future to realize flexible movements in indoor environments. The next three papers focus on audiovisual sensing to localize and navigate a robot. The second paper, entitled ""High-Speed Measurement of Normal Wall Direction by Ultrasonic Sensor,"" by A. Ohya et al., proposes a method to measure the normal direction of walls by ultrasonic array sensor. The third paper, entitled ""Self-Position Detection System Using a Visual-Sensor for Mobile Robots,"" is written by T. Tanaka et al. In their method, the position of the robot is decided by measuring marks such as name plates and fire alarm lamps by visual sensor. In the fourth paper, entitled ""Development of Ultra-Wide-Angle Laser Range Sensor and Navigation of a Mobile Robot in a Corridor Environment,"" written by Y Ando et al., a very wide view-angle sensor is realized using 5 laser fan beam projectors and 3 CCD cameras. The next three papers discussing navigation problems. The fifth paper, entitled ""Autonomous Navigation of an Intelligent Vehicle Using 1-Dimensional Optical Flow,"" by M. Yamada and K. Nakazawa, discusses navigation based on visual feedback. In this work, navigation is realized by general and qualitative knowledge of the environment. The sixth paper, entitled ""Development of Sensor-Based Navigation for Mobile Robots Using Target Direction Sensor,"" by M. Yamamoto et al., proposes a new sensor-based navigation algorithm in an unknown obstacle environment. The seventh paper, entitled ""Navigation Based on Vision and DGPS Information for Mobile Robots,"" S. Kotani et al., describes a navigation system for an autonomous mobile robot in an outdoor environment. The unique point of their paper is the utilization of landmarks and a differential global positioning system to determine robot position and orientation. The last paper deals with the relationship between the mobile robot and computer networks. The paper, entitled ""Direct Mobile Robot Teleoperation via Internet,"" by K. Kawabata et al., proposes direct teleoperation of a mobile robot via the Internet. Such network-based robotics will be an important field in robotics application. We sincerely thank all of the contributors to this special issue for their cooperation from the planning stage to the review process. Many thanks also go to the reviewers for their excellent work. We will be most happy if this issue aids readers in understanding recent trends in mobile robot research and furthers interest in this research field.

Real-time obstacle avoidance for multiple mobile robots

Robotica ◽  
2009 ◽  
Vol 27 (2) ◽  
pp. 189-198 ◽  
Author(s):  
Farbod Fahimi ◽  
C. Nataraj ◽  
Hashem Ashrafiuon
Keyword(s):  
Mobile Robots ◽  
Real Time ◽  
Obstacle Avoidance ◽  
Panel Method ◽  
The Other ◽  
Harmonic Potential ◽  
Current Position ◽  
Multiple Mobile Robots ◽  
Moving Obstacles ◽  
Harmonic Potential Field

SUMMARYAn efficient, simple, and practical real time path planning method for multiple mobile robots in dynamic environments is introduced. Harmonic potential functions are utilized along with the panel method known in fluid mechanics. First, a complement to the traditional panel method is introduced to generate a more effective harmonic potential field for obstacle avoidance in dynamically changing environments. Second, a group of mobile robots working in an environment containing stationary and moving obstacles is considered. Each robot is assigned to move from its current position to a goal position. The group is not forced to maintain a formation during the motion. Every robot considers the other robots of the group as moving obstacles and hence the physical dimensions of the robots are also taken into account. The path of each robot is planned based on the changing position of the other robots and the position of stationary and moving obstacles. Finally, the effectiveness of the scheme is shown by modeling an arbitrary number of mobile robots and the theory is validated by several computer simulations and hardware experiments.

Autonomous mobile robot navigation between static and dynamic obstacles using multiple ANFIS architecture

2019 ◽  
Vol 16 (2) ◽  
pp. 275-286 ◽  
Author(s):  
Anish Pandey ◽  
Abhishek Kumar Kashyap ◽  
Dayal R. Parhi ◽  
B.K. Patle
Keyword(s):  
Mobile Robot ◽  
Robot Navigation ◽  
Experimental Studies ◽  
Sensor Data ◽  
Mobile Robot Navigation ◽  
Control Technique ◽  
Inference System ◽  
Content Type ◽  
Moving Obstacles ◽  
Moving Obstacle

PurposeThis paper aims to design and implement the multiple adaptive neuro-fuzzy inference system (MANFIS) architecture-based sensor-actuator (motor) control technique for mobile robot navigation in different two-dimensional environments with the presence of static and moving obstacles.Design/methodology/approachThe three infrared range sensors have been mounted on the front, left and right side of the robot, which reads the forward, left forward and right forward static and dynamic obstacles in the environment. This sensor data information is fed as inputs into the MANFIS architecture to generate appropriate speed control commands for right and left motors of the robot. In this study, we have taken one assumption for moving obstacle avoidance in different scenarios the speed of the mobile robot is at least greater than or equal to the speed of moving obstacles and goal.FindingsGraphical simulations have designed through MATLAB and virtual robot experimentation platform (V-REP) software and experiments have been done on Arduino MEGA 2560 microcontroller-based mobile robot. Simulation and experimental studies demonstrate the effectiveness and efficiency of the proposed MANFIS architecture.Originality/valueThis paper designs and implements MANFIS architecture for mobile robot navigation between a static and moving obstacle in different simulation and experimental environments. Also, the authors have compared this developed architecture to the other navigational technique and found that our developed architecture provided better results in terms of path length in the same environment.

scholarly journals Method for SLAM Based on Omnidirectional Vision: A Delayed-EKF Approach

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Rodrigo Munguía ◽  
Carlos López-Franco ◽  
Emmanuel Nuño ◽  
Adriana López-Franco
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Autonomous Navigation ◽  
Real Data ◽  
Omnidirectional Vision ◽  
Wide Field ◽  
Visual Sensor ◽  
Cluttered Environments ◽  
Localization And Mapping ◽  
Wide Field Of View

This work presents a method for implementing a visual-based simultaneous localization and mapping (SLAM) system using omnidirectional vision data, with application to autonomous mobile robots. In SLAM, a mobile robot operates in an unknown environment using only on-board sensors to simultaneously build a map of its surroundings, which it uses to track its position. The SLAM is perhaps one of the most fundamental problems to solve in robotics to build mobile robots truly autonomous. The visual sensor used in this work is an omnidirectional vision sensor; this sensor provides a wide field of view which is advantageous in a mobile robot in an autonomous navigation task. Since the visual sensor used in this work is monocular, a method to recover the depth of the features is required. To estimate the unknown depth we propose a novel stochastic triangulation technique. The system proposed in this work can be applied to indoor or cluttered environments for performing visual-based navigation when GPS signal is not available. Experiments with synthetic and real data are presented in order to validate the proposal.

Study on Improved APF Algorithm for Autonomous Mobile Robot

2014 ◽  
Vol 519-520 ◽  
pp. 1337-1341 ◽  
Author(s):  
Xiao Meng Shu ◽  
Da Ming Jiang ◽  
Lian Dai
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Real Time ◽  
Obstacle Avoidance ◽  
Local Minimum ◽  
Minimum Point ◽  
Autonomous Mobile Robot ◽  
Simulation Environment ◽  
Local Minimum Point

In algorithms of obstacle avoidance for autonomous mobile robot, APF algorithm is simple, real-time and smooth, but has some limitations for solving problems. For example, the local minimum point may trap mobile robots before reaching its goal. Even though many improved APF algorithms have been put forward, few articles describe the process in detail to show how these algorithms are applied. Considering above factors, this paper focuses on embodiment of abstract improved theory for APF algorithm by showing some changes with formulas and parameters. The whole work has been done in simulation environment. According to the results this paper draws a conclusion.

NAVIGATION AMONG MOVABLE OBSTACLES: REAL-TIME REASONING IN COMPLEX ENVIRONMENTS

2005 ◽  
Vol 02 (04) ◽  
pp. 479-503 ◽  
Author(s):  
MIKE STILMAN ◽  
JAMES J. KUFFNER
Keyword(s):  
Mobile Robots ◽  
State Space ◽  
Real Time ◽  
Heuristic Search ◽  
Free Space ◽  
Single Agent ◽  
Complex Environments ◽  
Moving Obstacles ◽  
Large Numbers ◽  
Object Domain

In this paper, we address the problem of Navigation Among Movable Obstacles (NAMO): a practical extension to navigation for humanoids and other dexterous mobile robots. The robot is permitted to reconfigure the environment by moving obstacles and clearing free space for a path. This paper presents a resolution complete planner for a subclass of NAMO problems. Our planner takes advantage of the navigational structure through state-space decomposition and heuristic search. The planning complexity is reduced to the difficulty of the specific navigation task, rather than the dimensionality of the multi-object domain. We demonstrate real-time results for spaces that contain large numbers of movable obstacles. We also present a practical framework for single-agent search that can be used in algorithmic reasoning about this domain.

Path Planning for Mobile Robot Based on Autoregressive Model

2013 ◽  
Vol 431 ◽  
pp. 269-274
Author(s):  
Chuang Feng Huai ◽  
Xue Yan Jia
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Real Time ◽  
Autoregressive Model ◽  
Planning Process ◽  
Local Planning ◽  
Uncertain Environment ◽  
Motion Trajectories ◽  
Moving Obstacles ◽  
Global Planning

Proposed an uncertain environment path planning method for mobile robot in the presence of moving obstacles. Combining the global planning with the local planning, this dissertation presents a new approach to on-line real-time path planning with respect to the dynamic uncertain environment. With current sampling position, the autoregressive model predicts motion trajectories of moving obstacles. And the predicted positions are treated as instantaneously static. So moving obstacles in the predicted positions can be considered as static in the path planning process. Simulation examples demonstrated the effectiveness, feasibility, real-time capability, high stability and perfect performance of obstacle avoidance.

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