Search results

1 – 10 of over 1000
Article
Publication date: 25 February 2021

Hualei Zhang and Mohammad Asif Ikbal

In response to these shortcomings, this paper proposes a dynamic obstacle detection and tracking method based on multi-feature fusion and a dynamic obstacle recognition method…

Abstract

Purpose

In response to these shortcomings, this paper proposes a dynamic obstacle detection and tracking method based on multi-feature fusion and a dynamic obstacle recognition method based on spatio-temporal feature vectors.

Design/methodology/approach

The existing dynamic obstacle detection and tracking methods based on geometric features have a high false detection rate. The recognition methods based on the geometric features and motion status of dynamic obstacles are greatly affected by distance and scanning angle, and cannot meet the requirements of real traffic scene applications.

Findings

First, based on the geometric features of dynamic obstacles, the obstacles are considered The echo pulse width feature is used to improve the accuracy of obstacle detection and tracking; second, the space-time feature vector is constructed based on the time dimension and space dimension information of the obstacle, and then the support vector machine method is used to realize the recognition of dynamic obstacles to improve the obstacle The accuracy of object recognition. Finally, the accuracy and effectiveness of the proposed method are verified by real vehicle tests.

Originality/value

The paper proposes a dynamic obstacle detection and tracking method based on multi-feature fusion and a dynamic obstacle recognition method based on spatio-temporal feature vectors. The accuracy and effectiveness of the proposed method are verified by real vehicle tests.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 14 no. 2
Type: Research Article
ISSN: 1756-378X

Keywords

Article
Publication date: 7 February 2022

Toan Van Nguyen, Minh Hoang Do and Jaewon Jo

Collision avoidance is considered as a crucial issue in mobile robotic navigation to guarantee the safety of robots as well as working surroundings, especially for humans…

Abstract

Purpose

Collision avoidance is considered as a crucial issue in mobile robotic navigation to guarantee the safety of robots as well as working surroundings, especially for humans. Therefore, the position and velocity of obstacles appearing in the working space of the self-driving mobile robot should be observed to help the robot predict the collision and choose traversable directions. This paper aims to propose a new approach for obstacle tracking, dubbed MoDeT.

Design/methodology/approach

First, all long lines, such as walls, are extracted from the 2D-laser scan and considered as static obstacles (or mapped obstacles). Second, a density-based procedure is implemented to cluster nonwall obstacles. These clusters are then geometrically fitted as ellipses. Finally, the combination of Kalman filter and global nearest-neighbor (GNN) method is used to track obstacles’ position and velocity.

Findings

The proposed method (MoDeT) is experimentally verified by using an autonomous mobile robot (AMR) named AMR SR300. The MoDeT is found to provide better performance in comparison with previous methods for self-driving mobile robots.

Research limitations/implications

The robot can only see a part of the object, depending on the light detection and ranging scan view. As a consequence, geometrical features of the obstacle are sometimes changed, especially when the robot is moving fast.

Practical implications

This proposed method is to serve the navigation and path planning for the AMR.

Originality/value

(a) Proposing an extended weighted line extractor, (b) proposing a density-based obstacle detection and (c) implementing a combination of methods [in (a) and (b) constant acceleration Kalman and GNN] to obtain obstacles’ properties.

Details

Industrial Robot: the international journal of robotics research and application, vol. 49 no. 6
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 3 February 2020

Grant Rudd, Liam Daly and Filip Cuckov

This paper aims to present an intuitive control system for robotic manipulators that pairs a Leap Motion, a low-cost optical tracking and gesture recognition device, with the…

Abstract

Purpose

This paper aims to present an intuitive control system for robotic manipulators that pairs a Leap Motion, a low-cost optical tracking and gesture recognition device, with the ability to record and replay trajectories and operation to create an intuitive method of controlling and programming a robotic manipulator. This system was designed to be extensible and includes modules and methods for obstacle detection and dynamic trajectory modification for obstacle avoidance.

Design/methodology/approach

The presented control architecture, while portable to any robotic platform, was designed to actuate a six degree-of-freedom robotic manipulator of our own design. From the data collected by the Leap Motion, the manipulator was controlled by mapping the position and orientation of the human hand to values in the joint space of the robot. Additional recording and playback functionality was implemented to allow for the robot to repeat the desired tasks once the task had been demonstrated and recorded.

Findings

Experiments were conducted on our custom-built robotic manipulator by first using a simulation model to characterize and quantify the robot’s tracking of the Leap Motion generated trajectory. Tests were conducted in the Gazebo simulation software in conjunction with Robot Operating System, where results were collected by recording both the real-time input from the Leap Motion sensor, and the corresponding pose data. The results of these experiments show that the goal of accurate and real-time control of the robot was achieved and validated our methods of transcribing, recording and repeating six degree-of-freedom trajectories from the Leap Motion camera.

Originality/value

As robots evolve in complexity, the methods of programming them need to evolve to become more intuitive. Humans instinctively teach by demonstrating the task to a given subject, who then observes the various poses and tries to replicate the motions. This work aims to integrate the natural human teaching methods into robotics programming through an intuitive, demonstration-based programming method.

Details

Industrial Robot: the international journal of robotics research and application, vol. 47 no. 2
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 29 March 2019

Priyadarshi Biplab Kumar, Dayal R. Parhi and Chinmaya Sahu

With enhanced use of humanoids in demanding sectors of industrial automation and smart manufacturing, navigation and path planning of humanoid forms have become the centre of…

Abstract

Purpose

With enhanced use of humanoids in demanding sectors of industrial automation and smart manufacturing, navigation and path planning of humanoid forms have become the centre of attraction for robotics practitioners. This paper aims to focus on the development and implementation of a hybrid intelligent methodology to generate an optimal path for humanoid robots using regression analysis, adaptive particle swarm optimization and adaptive ant colony optimization techniques.

Design/methodology/approach

Sensory information regarding obstacle distances are fed to the regression controller, and an interim turning angle is obtained as the initial output. Adaptive particle swarm optimization technique is used to tune the governing parameter of adaptive ant colony optimization technique. The final output is generated by using the initial output of regression controller and tuned parameter from adaptive particle swarm optimization as inputs to the adaptive ant colony optimization technique along with other regular inputs. The final turning angle calculated from the hybrid controller is subsequently used by the humanoids to negotiate with obstacles present in the environment.

Findings

As the current investigation deals with the navigational analysis of single as well as multiple humanoids, a Petri-Net model has been combined with the proposed hybrid controller to avoid inter-collision that may happen in navigation of multiple humanoids. The hybridized controller is tested in simulation and experimental platforms with comparison of navigational parameters. The results obtained from both the platforms are found to be in coherence with each other. Finally, an assessment of the current technique with other existing navigational model reveals a performance improvement.

Research limitations/implications

The proposed hybrid controller provides satisfactory results for navigational analysis of single as well as multiple humanoids. However, the developed hybrid scheme can also be attempted with use of other smart algorithms.

Practical implications

Humanoid navigation is the present talk of the town, as its use is widespread to multiple sectors such as industrial automation, medical assistance, manufacturing sectors and entertainment. It can also be used in space and defence applications.

Social implications

This approach towards path planning can be very much helpful for navigating multiple forms of humanoids to assist in daily life needs of older adults and can also be a friendly tool for children.

Originality/value

Humanoid navigation has always been tricky and challenging. In the current work, a novel hybrid methodology of navigational analysis has been proposed for single and multiple humanoid robots, which is rarely reported in the existing literature. The developed navigational plan is verified through testing in simulation and experimental platforms. The results obtained from both the platforms are assessed against each other in terms of selected navigational parameters with observation of minimal error limits and close agreement. Finally, the proposed hybrid scheme is also evaluated against other existing navigational models, and significant performance improvements have been observed.

Details

Industrial Robot: the international journal of robotics research and application, vol. 46 no. 1
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 13 October 2021

Sharanabasappa and Suvarna Nandyal

In order to prevent accidents during driving, driver drowsiness detection systems have become a hot topic for researchers. There are various types of features that can be used to…

Abstract

Purpose

In order to prevent accidents during driving, driver drowsiness detection systems have become a hot topic for researchers. There are various types of features that can be used to detect drowsiness. Detection can be done by utilizing behavioral data, physiological measurements and vehicle-based data. The existing deep convolutional neural network (CNN) models-based ensemble approach analyzed the behavioral data comprises eye or face or head movement captured by using a camera images or videos. However, the developed model suffered from the limitation of high computational cost because of the application of approximately 140 million parameters.

Design/methodology/approach

The proposed model uses significant feature parameters from the feature extraction process such as ReliefF, Infinite, Correlation, Term Variance are used for feature selection. The features that are selected are undergone for classification using ensemble classifier.

Findings

The output of these models is classified into non-drowsiness or drowsiness categories.

Research limitations/implications

In this research work higher end camera are required to collect videos as it is cost-effective. Therefore, researches are encouraged to use the existing datasets.

Practical implications

This paper overcomes the earlier approach. The developed model used complex deep learning models on small dataset which would also extract additional features, thereby provided a more satisfying result.

Originality/value

Drowsiness can be detected at the earliest using ensemble model which restricts the number of accidents.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 15 no. 2
Type: Research Article
ISSN: 1756-378X

Keywords

Article
Publication date: 12 July 2022

Huaidong Zhou, Pengbo Feng and Wusheng Chou

Wheeled mobile robots (WMR) are the most widely used robots. Avoiding obstacles in unstructured environments, especially dynamic obstacles such as pedestrians, is a serious…

Abstract

Purpose

Wheeled mobile robots (WMR) are the most widely used robots. Avoiding obstacles in unstructured environments, especially dynamic obstacles such as pedestrians, is a serious challenge for WMR. This paper aims to present a hybrid obstacle avoidance method that combines an informed-rapidly exploring random tree* algorithm with a three-dimensional (3D)-object detection approach and model prediction controller (MPC) to conduct obstacle perception, collision-free path planning and obstacle avoidance for WMR in unstructured environments.

Design/methodology/approach

Given a reference orientation and speed, the hybrid method uses parametric ellipses to represent obstacle expansion boundaries based on the 3D target detection results, and a collision-free reference path is planned. Then, the authors build on a model predictive control for tracking the collision-free reference path by incorporating the distance between the robot and obstacles. The proposed framework is a mapless method for WMR.

Findings

The authors present experimental results with a mobile robot for obstacle avoidance in indoor environments crowded with obstacles, such as chairs and pedestrians. The results show that the proposed hybrid obstacle avoidance method can satisfy the application requirements of mobile robots in unstructured environments.

Originality/value

In this study, the parameter ellipse is used to represent the area occupied by the obstacle, which takes the velocity as the parameter. Therefore, the motion direction and position of dynamic obstacles can be considered in the planning stage, which enhances the success rate of obstacle avoidance. In addition, the distance between the obstacle and robot is increased in the MPC optimization function to ensure a safe distance between the robot and the obstacle.

Details

Industrial Robot: the international journal of robotics research and application, vol. 50 no. 1
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 12 June 2018

Mingming Guo, Hua Zhang, Chuncheng Feng, Manlu Liu and Jianwen Huo

This paper aims to present a method to improve the sensitive and low probabilities of false alarm of a manipulator in a human–robot interaction environment, which can improve the…

Abstract

Purpose

This paper aims to present a method to improve the sensitive and low probabilities of false alarm of a manipulator in a human–robot interaction environment, which can improve the performance of the system owing to non-linear uncertainty in the model of the robot controller.

Design/methodology/approach

A novel collision detection method based on adaptive residual estimation is proposed, promoting the detection accuracy of the collision of the manipulator during operation. First, a general momentum residual estimator is designed to incorporate the non-linear factors of the manipulator (e.g. joint friction, speed and acceleration) into the residual-related uncertainty of the model. Second, model parameters are estimated through gradient correction. The residual filter is used to determine the dynamic threshold, resulting in higher detection accuracy. Finally, the performance of the residual estimation scheme is evaluated by comparing the dynamic threshold with residual in real-time experiments where a single Universal Robot 5 robot end–effector collides with the obstacle.

Findings

Experimental results demonstrate that the collision detection system can improve sensitivity and lead to low probabilities of false alarm of non-linear uncertainty in the model.

Practical implications

The method proposed in this article can be applied to industry and human–robot interaction area.

Originality/value

An adaptive collision detection method is proposed in this paper to address non-linear uncertainties of the model in industrial application.

Details

Industrial Robot: An International Journal, vol. 45 no. 3
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 9 February 2018

Qiang Zhou, Danping Zou and Peilin Liu

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…

Abstract

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.

Details

Industrial Robot: An International Journal, vol. 45 no. 2
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 11 January 2022

Weiliang Zhu, Zhaojun Pang, Jiyue Si and Zhonghua Du

This paper aims to study the encounter issues of the Tethered-Space Net Robot System (TSNRS) with non-target objects on orbit during the maneuver, including the collision issues…

Abstract

Purpose

This paper aims to study the encounter issues of the Tethered-Space Net Robot System (TSNRS) with non-target objects on orbit during the maneuver, including the collision issues with small space debris and the obstacle avoidance from large obstacles.

Design/methodology/approach

For the collision of TSNRS with small debris, the available collision model of the tethered net and its limitation is discussed, and the collision detection method is improved. Then the dynamic response of TSNRS is studied and a closed-loop controller is designed. For the obstacle avoidance, the variable enveloping circle of the TSNRS has coupled with the artificial potential field (APF) method. In addition, the APF is improved with a local trajectory correction method to avoid the overbending segment of the trajectory.

Findings

The collision model coupled with the improved collision detection method solves the detection failure and speeds up calculation efficiency by 12 times. Collisions of TSNRS with small debris make the local thread stretch and deforms finally making the net a mess. The boundary of the disturbance is obtained by a series of collision tests, and the designed controller not only achieved the tracking control of the TSNRS but also suppressed the disturbance of the net.

Practical implications

This paper fills the gap in the research on the collision of the tethered net with small debris and makes the collision model more general and efficient by improving the collision detection method. And the coupled obstacle avoidance method makes the process of obstacle avoidance safer and smoother.

Originality/value

The work in this paper provides a reference for the on-orbit application of TSNRS in the active space debris removal mission.

Details

Aircraft Engineering and Aerospace Technology, vol. 94 no. 5
Type: Research Article
ISSN: 1748-8842

Keywords

Article
Publication date: 30 May 2019

Fengyu Xu and Quansheng Jiang

Field robots can surmount or avoid some obstacles when operating on rough ground. However, cable-climbing robots can only surmount obstacles because their moving path is…

Abstract

Purpose

Field robots can surmount or avoid some obstacles when operating on rough ground. However, cable-climbing robots can only surmount obstacles because their moving path is completely restricted along the cables. This paper aims to analyse the dynamic obstacle-surmounting models for the driving and driven wheels of the climbing mechanism, and design a mechanical structure for a bilateral-wheeled cable-climbing robot to improve the obstacle crossing capability.

Design/methodology/approach

A mechanical structure of the bilateral-wheeled cable-climbing robot is designed in this paper. Then, the kinematic and dynamic obstacle-surmounting of the driven and driving wheels are investigated through static-dynamic analysis and Lagrangian mechanical analysis, respectively. The climbing and obstacle-surmounting experiments are carried out to improve the obstacle crossing capability. The required motion curve, speed and driving moment of the robot during obstacle-surmounting are generated from the experiments results.

Findings

The presented method offers a solution for dynamic obstacle-surmounting analysis of a bilateral-wheeled cable-climbing robot. The simulation, laboratory testing and field experimental results prove that the climbing capability of the robot is near-constant on cables with diameters between 60 and 205 mm.

Originality/value

The dynamic analysis method presented in this paper is found to be applicable to rod structures with large obstacles and improved the stability of the robot at high altitude. Simulations and experiments are also conducted for performance evaluation.

Details

Industrial Robot: the international journal of robotics research and application, vol. 46 no. 3
Type: Research Article
ISSN: 0143-991X

Keywords

1 – 10 of over 1000