scholarly journals Obstacle Avoidance for Quadcopter using Ultrasonic Sensor

2018 ◽  
Vol 1005 ◽  
pp. 012037 ◽  
Author(s):  
Muhammad Fazlur Rahman ◽  
Rianto Adhy Sasongko
Keyword(s):  
Obstacle Avoidance ◽  
Ultrasonic Sensor

Research on the Design of Intelligent Obstacle Avoidance Car Model Based on Ultrasonic Wave

2013 ◽  
Vol 461 ◽  
pp. 531-534
Author(s):  
Yu Zhu ◽  
Zhe Xin Han ◽  
Peng Kun Sun ◽  
Tian Hao Wang ◽  
Yin Han Gao
Keyword(s):  
Ambient Temperature ◽  
Ultrasonic Wave ◽  
Obstacle Avoidance ◽  
External Environment ◽  
Ultrasonic Sensor ◽  
Design System ◽  
Intelligent Vehicle ◽  
The Core ◽  
Car Model ◽  
Model Based

Based on the characteristic of an ultrasonic sensor that can sense the external environment, we design an intelligent vehicle with obstacle avoidance function. First, we use MSP430 as the core of the design system. Second, we distribute the ultrasonic sensor evenly on the round zone of the obstacles to process the data and ambient temperature, which is transmitted from the ultrasonic receiver through the SCM (what is SCM, explain). Finally, we make it to realize the functions of intelligent controlling and avoiding obstacles automatically.

Hybrid obstacle avoidance system with vision and ultrasonic sensors for multi-rotor MAVs

2018 ◽  
Vol 45 (2) ◽  
pp. 227-236 ◽  
Author(s):  
Qiang Zhou ◽  
Danping Zou ◽  
Peilin Liu
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Moving Objects ◽  
Point Clouds ◽  
Ultrasonic Sensor ◽  
Content Type ◽  
Stereo Camera ◽  
3D Point Clouds ◽  
Planning Algorithm ◽  
Path Planning Algorithm

Purpose This paper aims to develop an obstacle avoidance system for a multi-rotor micro aerial vehicle (MAV) that flies in indoor environments which usually contain transparent, texture-less or moving objects. Design/methodology/approach The system adopts a combination of a stereo camera and an ultrasonic sensor to detect obstacles and extracts three-dimensional (3D) point clouds. The obstacle map is built on a coarse global map and updated by local maps generated by the recent 3D point clouds. An efficient layered A* path planning algorithm is also proposed to address the path planning in 3D space for MAVs. Findings The authors conducted a lot of experiments in both static and dynamic scenes. The results show that the obstacle avoidance system works reliably even when transparent or texture-less obstacles are present. The layered A* path planning algorithm is much faster than the traditional 3D algorithm and makes the system response quickly when the obstacle map has been changed because of the moving objects. Research limitations/implications The limited field of view of both stereo camera and ultrasonic sensor makes the system need to change heading first before moving side to side or moving backward. But this problem could be addressed when multiple systems are mounted toward different directions on the MAV. Practical implications The developed approach could be valuable to applications in indoors. Originality/value This paper presents a robust obstacle avoidance system and a fast layered path planning algorithm that are easy to be implemented for practical systems.

scholarly journals An IoT Based Obstacle Avoidance Robot Using Ultrasonic Sensor and Arduino

2020 ◽  
Vol 981 ◽  
pp. 042002
Author(s):  
Rajesh Mothe ◽  
S. Tharun Reddy ◽  
G. Sunil ◽  
Chintoju Sidhardha
Keyword(s):  
Obstacle Avoidance ◽  
Ultrasonic Sensor

Obstacle Avoidance System Based on Single Rotary Ultrasonic Sensor

2011 ◽  
Vol 55-57 ◽  
pp. 521-526
Author(s):  
Guang Zhao Cui ◽  
Wen Juan Wei ◽  
Jin Chao Guo
Keyword(s):  
Data Processing ◽  
Obstacle Avoidance ◽  
Horizontal Plane ◽  
Ultrasonic Sensor ◽  
Experimental Results ◽  
Stepper Motor ◽  
World Model ◽  
Safe Area ◽  
Round Obstacle ◽  
Avoidance Problem

Centering round obstacle avoidance problem, an evadible system based on the ultrasonic sensor Sens600 is presented in this paper, the sensor rotated by the stepper motor scans back and forth in horizontal plane ahead of the robot, then the system builds and updates a histogram world model with the to-and-fro range information after data processing, the safe area capture (SAC) method is applied to compute the most suitable direction among all candidates, and the steering of the robot is aligned with that direction. The experimental results demonstrate the feasibility and effectiveness of the proposed system.

scholarly journals Obstacle Avoidance of Multi-Sensor Intelligent Robot Based on Road Sign Detection

Sensors ◽  
2021 ◽  
Vol 21 (20) ◽  
pp. 6777
Author(s):  
Jianwei Zhao ◽  
Jianhua Fang ◽  
Shouzhong Wang ◽  
Kun Wang ◽  
Chengxiang Liu ◽  
...  
Keyword(s):  
Obstacle Avoidance ◽  
Visual Information ◽  
Ultrasonic Sensor ◽  
Intelligent Robot ◽  
Distance Information ◽  
The Road ◽  
Additional Information ◽  
Road Signs ◽  
Road Sign ◽  
Control Command

The existing ultrasonic obstacle avoidance robot only uses an ultrasonic sensor in the process of obstacle avoidance, which can only be avoided according to the fixed obstacle avoidance route. Obstacle avoidance cannot follow additional information. At the same time, existing robots rarely involve the obstacle avoidance strategy of avoiding pits. In this study, on the basis of ultrasonic sensor obstacle avoidance, visual information is added so the robot in the process of obstacle avoidance can refer to the direction indicated by road signs to avoid obstacles, at the same time, the study added an infrared ranging sensor, so the robot can avoid potholes. Aiming at this situation, this paper proposes an intelligent obstacle avoidance design of an autonomous mobile robot based on a multi-sensor in a multi-obstruction environment. A CascadeClassifier is used to train positive and negative samples for road signs with similar color and shape. A multi-sensor information fusion is used for path planning and the obstacle avoidance logic of the intelligent robot is designed to realize autonomous obstacle avoidance. The infrared sensor is used to obtain the environmental information of the ground depression on the wheel path, the ultrasonic sensor is used to obtain the distance information of the surrounding obstacles and road signs, and the information of the road signs obtained by the camera is processed by the computer and transmitted to the main controller. The environment information obtained is processed by the microprocessor and the control command is output to the execution unit. The feasibility of the design is verified by analyzing the distance acquired by the ultrasonic sensor, infrared distance measuring sensors, and the model obtained by training the sample of the road sign, as well as by experiments in the complex environment constructed manually.

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