Design and Fabrication of an Autonomous Mobile Robot for Obstacle Avoidance and Path Planning in Partially Known Environment

2011 ◽  
Vol 403-408 ◽  
pp. 3917-3924
Author(s):  
Deep Sharma ◽  
S. K. Dwivedy
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Low Cost ◽  
Dc Motor ◽  
Outdoor Environment ◽  
Autonomous Mobile Robot ◽  
Solar Panels ◽  
Dc Motors ◽  
Servo Controller

In this paper, an autonomous mobile robot has been designed and fabricated which can be used in both indoor and outdoor for industrial and household applications. Here using six servo motors and four DC motors with their controllers (servo controller and L293D DC Motor controller) the mobile robot can pick any object from its workspace and by avoiding collision it can place the object in the desired location. ASCII ultrasonic sensor and motion sensor are used along with ATmega 2560 microcontroller which is programmed to take the sensors output as its input and controls the dc motor and servo motors to pick and place objects and avoid obstacle during motion of the mobile robot. Here low-cost solar panels have been used to recharge the Li-ion batteries used for the motors and microcontroller in case of outdoor environment. The obstacle avoidance and path planning algorithms have been developed and a case study has been presented in this paper.

scholarly journals 3 Bio-Mimetic Vision System For Autonomous Mobile Robot Navigation

2013 ◽  
Vol 3 (1) ◽  
pp. 4
Author(s):  
Muhammad Safwan ◽  
Muhammad Yasir Zaheen ◽  
M. Anwar Ahmed ◽  
Muhammad Shujaat Kamal ◽  
Raj Kumar
Keyword(s):  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Stereo Vision ◽  
Robot Navigation ◽  
Vision System ◽  
Experimental Results ◽  
Mobile Robot Navigation ◽  
Absolute Difference ◽  
Autonomous Mobile Robot ◽  
Dc Motors

Bio-Mimetic Vision System (BMVS) for AutonomousMobile Robot Navigation encompasses three major fields, namelyrobotics, navigation and obstacle avoidance. Bio-mimetic vision isbased on stereo vision. Summation of Absolute Difference (SAD)is applied on the images from the two cameras and disparity mapis generated which is then used to navigate and avoid obstacles.Camera calibration and SAD is applied on Matlab software.AT89C52 microcontroller, along with Matlab, is used to efficientlycontrol the DC motors mounted on the robot frame. It is observedfrom experimental results that the developed system effectivelydistinguishes objects at different distances and avoids them whenthe path is blocked.

3D X-Y-T Space Path Planning for Autonomous Mobile Robots Considering Dynamic Constraints

2014 ◽  
Vol 490-491 ◽  
pp. 1163-1167 ◽  
Author(s):  
Ippei Nishitani ◽  
Tetsuya Matsumura ◽  
Mayumi Ozawa ◽  
Ayanori Yorozu ◽  
Masaki Takahashi
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Personal Space ◽  
Free Motion ◽  
Autonomous Mobile Robot ◽  
Dynamic Constraints ◽  
Living Space ◽  
Look Ahead ◽  
Laser Range Finders

An autonomous mobile robot in a human living space should be able to not only realize collision-free motion but also give way to humans depending on the situation. Although various reactive obstacle avoidance methods have been proposed, it is difficult to achieve such motion. On the other hand, 3D X-Y-T space path planning, which takes into account the motion of both the robot and the human in a look-ahead time horizon, is effective. This paper proposes a real-time obstacle avoidance method for an autonomous mobile robot that considers the robots dynamic constraints, the personal space, and human directional area based on grid-based 3D X-Y-T space path planning. The proposed method generates collision-free motion in which the robot can yield to humans. To verify the effectiveness of the proposed method, various experiments in which the humans position and velocity were estimated using laser range finders were carried out.

scholarly journals 3 Bio-Mimetic Vision System For Autonomous Mobile Robot Navigation

2013 ◽  
Vol 1 (1) ◽  
pp. 4
Author(s):  
Muhammad Safwan ◽  
Muhammad Yasir Zaheen ◽  
M. Anwar Ahmed ◽  
Muhammad Shujaat Kamal ◽  
Raj Kumar
Keyword(s):  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Stereo Vision ◽  
Robot Navigation ◽  
Vision System ◽  
Experimental Results ◽  
Mobile Robot Navigation ◽  
Absolute Difference ◽  
Autonomous Mobile Robot ◽  
Dc Motors

Bio-Mimetic Vision System (BMVS) for AutonomousMobile Robot Navigation encompasses three major fields, namelyrobotics, navigation and obstacle avoidance. Bio-mimetic vision isbased on stereo vision. Summation of Absolute Difference (SAD)is applied on the images from the two cameras and disparity mapis generated which is then used to navigate and avoid obstacles.Camera calibration and SAD is applied on Matlab software.AT89C52 microcontroller, along with Matlab, is used to efficientlycontrol the DC motors mounted on the robot frame. It is observedfrom experimental results that the developed system effectivelydistinguishes objects at different distances and avoids them whenthe path is blocked.

Vision-based obstacle avoidance system for autonomous mobile robot in outdoor environment

ICCAS 2010 ◽  
2010 ◽  
Author(s):  
Ji Eun Jung ◽  
Kil Soo Lee ◽  
Hyung Gyu Park ◽  
Yung Ho Koh ◽  
Jong Il Bae ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Outdoor Environment ◽  
Autonomous Mobile Robot

FUZZY COGNITIVE MAPS EMBEDDED IN A LOW COST AUTONOMOUS MOBILE ROBOT

2019 ◽  
Author(s):  
Márcio Mendonça ◽  
Guilherme Bender Sartori ◽  
Lucas Botoni de Souza ◽  
Giovanni Bruno Marquini Ribeiro
Keyword(s):  
Mobile Robot ◽  
Low Cost ◽  
Cognitive Maps ◽  
Fuzzy Cognitive Maps ◽  
Autonomous Mobile Robot

scholarly journals Research on path planning of three-neighbor search A* algorithm combined with artificial potential field

2021 ◽  
Vol 18 (3) ◽  
pp. 172988142110264
Author(s):  
Jiqing Chen ◽  
Chenzhi Tan ◽  
Rongxian Mo ◽  
Hongdu Zhang ◽  
Ganwei Cai ◽  
...  
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Potential Field ◽  
Path Length ◽  
Search Time ◽  
Experimental Results ◽  
Artificial Potential Field ◽  
A Algorithm ◽  
Neighbor Search

Among the shortcomings of the A* algorithm, for example, there are many search nodes in path planning, and the calculation time is long. This article proposes a three-neighbor search A* algorithm combined with artificial potential fields to optimize the path planning problem of mobile robots. The algorithm integrates and improves the partial artificial potential field and the A* algorithm to address irregular obstacles in the forward direction. The artificial potential field guides the mobile robot to move forward quickly. The A* algorithm of the three-neighbor search method performs accurate obstacle avoidance. The current pose vector of the mobile robot is constructed during obstacle avoidance, the search range is narrowed to less than three neighbors, and repeated searches are avoided. In the matrix laboratory environment, grid maps with different obstacle ratios are compared with the A* algorithm. The experimental results show that the proposed improved algorithm avoids concave obstacle traps and shortens the path length, thus reducing the search time and the number of search nodes. The average path length is shortened by 5.58%, the path search time is shortened by 77.05%, and the number of path nodes is reduced by 88.85%. The experimental results fully show that the improved A* algorithm is effective and feasible and can provide optimal results.

Fuzzy Logic Controller for Obstacle Avoidance of Mobile Robot

2019 ◽  
Vol 20 (1) ◽  
pp. 51-62
Author(s):  
Rajmeet Singh ◽  
Tarun Kumar Bera
Keyword(s):  
Fuzzy Logic ◽  
Mobile Robot ◽  
Dynamic Model ◽  
Obstacle Avoidance ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Bond Graph ◽  
Membership Functions ◽  
Current Position ◽  
Dc Motors

AbstractThis work describes design and implementation of a navigation and obstacle avoidance controller using fuzzy logic for four-wheel mobile robot. The main contribution of this paper can be summarized in the fact that single fuzzy logic controller can be used for navigation as well as obstacle avoidance (static, dynamic and both) for dynamic model of four-wheel mobile robot. The bond graph is used to develop the dynamic model of mobile robot and then it is converted into SIMULINK block by using ‘S-function’ directly from SYMBOLS Shakti bond graph software library. The four-wheel mobile robot used in this work is equipped with DC motors, three ultrasonic sensors to measure the distance from the obstacles and optical encoders to provide the current position and speed. The three input membership functions (distance from target, angle and distance from obstacles) and two output membership functions (left wheel voltage and right wheel voltage) are considered in fuzzy logic controller. One hundred and sixty-two sets of rules are considered for motion control of the mobile robot. The different case studies are considered and are simulated using MATLAB-SIMULINK software platform to evaluate the performance of the controller. Simulation results show the performances of the navigation and obstacle avoidance fuzzy controller in terms of minimum travelled path for various cases.

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