Obstacle Detection and Avoidance Using Wavefront Planner and Kinect on a WMRA

2012 ◽  
Author(s):  
Ivan Shindev ◽  
Shane Marlin ◽  
Nathan Preseault ◽  
Rodrigo Tamayo ◽  
William Pence ◽  
...  
Keyword(s):  
Obstacle Avoidance ◽  
Autonomous Navigation ◽  
Obstacle Detection ◽  
Robotic Arm ◽  
Accurate Representation ◽  
Start Position ◽  
Autonomous Operation ◽  
Suitable Solution ◽  
Navigation Control ◽  
Wheelchair Mounted Robotic Arm

Obstacle avoidance in autonomous navigation platforms is a well known problem that can be solved in numerous ways. This paper considers and analyzes the use of wavefront planner as an obstacle avoidance algorithm for a 9-DoF wheelchair-mounted robotic arm (WMRA) [1]. It also presents a suitable solution for obstacle detection using the OpenNI driver for interfacing with Microsoft’s Kinect. It further analyzes the capabilities of an autonomous operation of the WMRA and explains how this algorithm can be implemented into its navigation control. The results of this project showed that the Kinect can provide a very accurate representation of the surroundings. The wavefront planner can use this data to find a path from a start position to a goal without running into an obstacle.

scholarly journals Vision-Based Moving Obstacle Detection and Tracking in Paddy Field Using Improved Yolov3 and Deep SORT

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4082 ◽  
Author(s):  
Zhengjun Qiu ◽  
Nan Zhao ◽  
Lei Zhou ◽  
Mengcen Wang ◽  
Liangliang Yang ◽  
...  
Keyword(s):  
Obstacle Avoidance ◽  
Processing Speed ◽  
Paddy Field ◽  
Autonomous Navigation ◽  
Vision System ◽  
Obstacle Detection ◽  
Paddy Fields ◽  
Future Research ◽  
Moving Obstacles ◽  
Agricultural Machines

Using intelligent agricultural machines in paddy fields has received great attention. An obstacle avoidance system is required with the development of agricultural machines. In order to make the machines more intelligent, detecting and tracking obstacles, especially the moving obstacles in paddy fields, is the basis of obstacle avoidance. To achieve this goal, a red, green and blue (RGB) camera and a computer were used to build a machine vision system, mounted on a transplanter. A method that combined the improved You Only Look Once version 3 (Yolov3) and deep Simple Online and Realtime Tracking (deep SORT) was used to detect and track typical moving obstacles, and figure out the center point positions of the obstacles in paddy fields. The improved Yolov3 has 23 residual blocks and upsamples only once, and has new loss calculation functions. Results showed that the improved Yolov3 obtained mean intersection over union (mIoU) score of 0.779 and was 27.3% faster in processing speed than standard Yolov3 on a self-created test dataset of moving obstacles (human and water buffalo) in paddy fields. An acceptable performance for detecting and tracking could be obtained in a real paddy field test with an average processing speed of 5–7 frames per second (FPS), which satisfies actual work demands. In future research, the proposed system could support the intelligent agriculture machines more flexible in autonomous navigation.

Obstacle Avoidance and Navigation of Autonomous Mobile Robot

2011 ◽  
Vol 403-408 ◽  
pp. 4633-4642 ◽  
Author(s):  
Rekha Raja ◽  
S N. Shome ◽  
S. Nandy ◽  
R. Ray
Keyword(s):  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Autonomous Navigation ◽  
Fuzzy Logic Controller ◽  
Classical Method ◽  
Obstacle Detection ◽  
Autonomous Mobile Robot ◽  
Unstructured Environment ◽  
Multiple Obstacles ◽  
Robot Platform

This paper presents a hybrid obstacle avoidance methodology for autonomous navigation of a mobile robot in an unstructured environment. Decision is taken based on the classical method depending on the environmental scenario where the space between multiple obstacles is measured and the feasibility of passing the robot through any immediate pair of obstacles examined. In other cases, the decision is taken by the Fuzzy Logic controller. The developed algorithm is simulated and experimentally validated with a mobile robot platform equipped with forward-looking sonar for obstacle detection. Odometry sensors assist in localization of the mobile robot. The developed algorithm is found adequately intelligent to navigate the robot from any start position through to the desired goal position avoiding obstacles, and without taking recourse to any pre-built map. The simulated results exhibit fair agreement with the experimental results.

Autonomous Navigation and Obstacle Avoidance

2009 ◽  
Author(s):  
Jesse Berger ◽  
Cory Carson ◽  
Massood Towhidnejad ◽  
Richard Stansbury
Keyword(s):  
Obstacle Avoidance ◽  
Autonomous Navigation

scholarly journals A State-of-the-Art Analysis of Obstacle Avoidance Methods from the Perspective of an Agricultural Sprayer UAV’s Operation Scenario

Agronomy ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1069
Author(s):  
Shibbir Ahmed ◽  
Baijing Qiu ◽  
Fiaz Ahmad ◽  
Chun-Wei Kong ◽  
Huang Xin
Keyword(s):  
Collision Avoidance ◽  
Obstacle Avoidance ◽  
State Of The Art ◽  
Obstacle Detection ◽  
Crop Monitoring ◽  
Data Intensive ◽  
Structural Details ◽  
Dynamic Operating ◽  
New Generation ◽  
The Internet Of Things

Over the last decade, Unmanned Aerial Vehicles (UAVs), also known as drones, have been broadly utilized in various agricultural fields, such as crop management, crop monitoring, seed sowing, and pesticide spraying. Nonetheless, autonomy is still a crucial limitation faced by the Internet of Things (IoT) UAV systems, especially when used as sprayer UAVs, where data needs to be captured and preprocessed for robust real-time obstacle detection and collision avoidance. Moreover, because of the objective and operational difference between general UAVs and sprayer UAVs, not every obstacle detection and collision avoidance method will be sufficient for sprayer UAVs. In this regard, this article seeks to review the most relevant developments on all correlated branches of the obstacle avoidance scenarios for agricultural sprayer UAVs, including a UAV sprayer’s structural details. Furthermore, the most relevant open challenges for current UAV sprayer solutions are enumerated, thus paving the way for future researchers to define a roadmap for devising new-generation, affordable autonomous sprayer UAV solutions. Agricultural UAV sprayers require data-intensive algorithms for the processing of the images acquired, and expertise in the field of autonomous flight is usually needed. The present study concludes that UAV sprayers are still facing obstacle detection challenges due to their dynamic operating and loading conditions.

scholarly journals Autonomous system to control a mobile robot

2020 ◽  
Vol 9 (4) ◽  
pp. 1711-1717
Author(s):  
Ayman Abu Baker ◽  
Yazeed Yasin Ghadi
Keyword(s):  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Autonomous Navigation ◽  
Fuzzy Controller ◽  
Computational Time ◽  
Ongoing Effort ◽  
Unstructured Environment ◽  
Adaptive Inference ◽  
Real Time Applications ◽  
Linguistic Labels

This paper presents an ongoing effort to control a mobile robot in unstructured environment. 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 paper, the fuzzy controller is used to tackle the problem of mobile robot autonomous navigation in unstructured environment. The objective is to make the robot move along a collision free trajectory until it reaches its target. The proposed approach uses the fuzzified, adaptive inference engine and defuzzification engine. Also number of linguistic labels is optimized for the input of the mobile robot in order to reduce computational time for real-time applications. The proposed fuzzy controller is evaluated subjectively and objectively with other approaches and also the processing time is taken in consideration.

scholarly journals A Hands-Free Obstacle Detection and Avoidance System

2015 ◽  
Vol 5 (3) ◽  
pp. 801-804
Author(s):  
M. Abdul-Niby ◽  
M. Alameen ◽  
O. Irscheid ◽  
M. Baidoun ◽  
H. Mourtada
Keyword(s):  
Obstacle Avoidance ◽  
Visually Impaired ◽  
Low Cost ◽  
Cost Effective ◽  
Obstacle Detection ◽  
Text To Speech ◽  
Voice Signal ◽  
Visually Impaired People ◽  
Impaired People ◽  
The Voice

In this paper, we present a low cost hands-free detection and avoidance system designed to provide mobility assistance for visually impaired people. An ultrasonic sensor is attached to the jacket of the user and detects the obstacles in front. The information obtained is transferred to the user through audio messages and also by a vibration. The range of the detection is user-defined. A text-to-speech module is employed for the voice signal. The proposed obstacle avoidance device is cost effective, easy to use and easily upgraded.

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