Obstacle detection for autonomous systems using stereoscopic images and bacterial behaviour

Sarmiento, Fredy Hernán Martínez; Jacinto, Edwar; Martínez, Fernando

doi:10.11591/ijece.v10i2.pp2164-2172

Cited by 7 publications

(10 citation statements)

References 15 publications

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“…Avoiding obstacles in local route planning is an essential technology and one of an important technology that guarantees safety. Robot navigation is the ability of a mobile robot for moving around environment (the known as well as the unknown) in which the goal can be achieved without hitting any obstacle [2], [48] this process requires a map, target location, and current location of the robot using a sensor or other positioning system. In addition, recalculate detouring path and for steering itself to a more efficient and safer path in the real time.…”

Section: Obstacle Avoidancementioning

confidence: 99%

“…Therefore, the algorithm of obstacle avoidance is helpful in preventing the collisions. These include obstacle detection and the actual obstacle avoidance [4], [47], [48]. Most of the prevent collisions algorithms can be: a. Map-based: this type of the algorithm depends upon the geometric models or the maps of an environment.…”

Section: Obstacle Avoidancementioning

confidence: 99%

“…One of the main disadvantages of this type of algorithm is that the behavior of robots at certain times is usually a function that only considers the latest sensor readings. This can cause unwanted problems but can be prevented if a momentary reading of the robot sensor does not provide enough information to avoid collisions [2], [6], [48]. b.…”

Section: Obstacle Avoidancementioning

confidence: 99%

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A one decade survey of autonomous mobile robot systems

Zghair

Al-Araji

2021

IJECE

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<span lang="EN-US">Recently, autonomous mobile robots have gained popularity in the modern world due to their relevance technology and application in real world situations. The global market for mobile robots will grow significantly over the next 20 years. Autonomous mobile robots are found in many fields including institutions, industry, business, hospitals, agriculture as well as private households for the purpose of improving day-to-day activities and services. The development of technology has increased in the requirements for mobile robots because of the services and tasks provided by them, like rescue and research operations, surveillance, carry heavy objects and so on. Researchers have conducted many works on the importance of robots, their uses, and problems. This article aims to analyze the control system of mobile robots and the way robots have the ability of moving in real-world to achieve their goals. It should be noted that there are several technological directions in a mobile robot industry. It must be observed and integrated so that the robot functions properly: Navigation systems, localization systems, detection systems (sensors) along with motion and kinematics and dynamics systems. All such systems should be united through a control unit; thus, the mission or work of mobile robots are conducted with reliability.</span>

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Section: Obstacle Avoidancementioning

confidence: 99%

Section: Obstacle Avoidancementioning

confidence: 99%

Section: Obstacle Avoidancementioning

confidence: 99%

See 1 more Smart Citation

A one decade survey of autonomous mobile robot systems

Zghair

Al-Araji

2021

IJECE

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“…Also, a laser system can establish distances to an obstacle point, but sweeps are required to establish the general topology of the obstacle [25]. The second trend is supported by passive methods, which estimate the location of the obstacle by processing the information recorded in two stereoscopic images [21,26]. Traditionally these images are processed digitally and allow a certain degree of independence concerning the type of cameras required.…”

Section: Citie-2021 Journal Of Physics: Conference Series 2135 (2021) 012002mentioning

confidence: 99%

Parallel control model for navigation tasks on service robots

Ariza

Martínez

Sarmiento

2021

J. Phys.: Conf. Ser.

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Autonomous mobility remains an open research problem in robotics. This is a complex problem that has its characteristics according to the type of task and environment intended for the robot’s activity. Service robotics has in this sense problems that have not been solved satisfactorily. These robots must interact with human beings in environments designed for human beings, which implies that one of the basic sensors for structuring motion control and navigation schemes are those that replicate the human optical sense. In their normal activity, robots are expected to interpret visual information in the environment while following a certain motion policy that allows them to move from one point to another in the environment, consistent with their tasks. A good optical sensing system can be structured around digital cameras, with which it can apply visual identification routines of both the trajectory and its environment. This research proposes a parallel control scheme (with two loops) for the definition of movements of a service robot from images. On the one hand, there is a control loop based on a visual memory strategy using a convolutional neural network. This system contemplates a deep learning model that is trained from images of the environment containing characteristic elements of the navigation environment (various types of obstacles and different cases of free trajectories with and without navigation path). To this first loop is connected in parallel a second loop in charge of defining the specific distances to the obstacles using a stereo vision system. The objective of this parallel loop is to quickly identify the obstacle points in front of the robot from the images using a bacterial interaction model. These two loops form an information feedback motion control framework that quickly analyzes the environment and defines motion strategies from digital images, achieving real-time control driven by visual information. Among the advantages of our scheme are the low processing and memory costs in the robot, and the no need to modify the environment to facilitate the navigation of the robot. The performance of the system is validated by simulation and laboratory experiments.

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“…Their proposed algorithm was capable to provide an error less than 5% during distance calculation. Martinez et al [8] measured the distance that separates the object from the camera in a straight line (0.3-2 m), and the obtained results were compared with actual values. Sun et al [18] built a vision system based on two cameras and the results obtained using the VS2013 environment have shown that the error is less than 5% for distances within 2 m. Distance values found from two experiments, one using a webcam rig and the other one using ZED camera, were compared in the work of Ref.…”

mentioning

confidence: 99%

A novel algorithm for distance measurement using stereo camera

Adil

Mikou

Mouhsen

2022

CAAI Trans on Intel Tech

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Distance estimation can be achieved by using active sensors or with the help of passive sensors such as cameras. The stereo vision system is generally composed of two cameras to mimic the human binocular vision. In this paper, a Python‐based algorithm is proposed to find the parameters of each camera, rectify the images, create the disparity maps and finally use these maps for distance measurements. Experiments using real‐time images, which were captured from our stereo vision system, of different obstacles positioned at multiple distances (60–200 cm) prove the effectiveness of the proposed program and show that the calculated distance to the obstacle is relatively accurate. The accuracy of distance measurement is up to 99.83%. The processing time needed to calculate the distance between the obstacle and the cameras is less than 0.355 s.

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Obstacle detection for autonomous systems using stereoscopic images and bacterial behaviour

Cited by 7 publications

References 15 publications

A one decade survey of autonomous mobile robot systems

A one decade survey of autonomous mobile robot systems

Parallel control model for navigation tasks on service robots

A novel algorithm for distance measurement using stereo camera

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