Search results

1 – 10 of 15
Article
Publication date: 27 April 2020

Saroj Kumar, Dayal R. Parhi, Manoj Kumar Muni and Krishna Kant Pandey

This paper aims to incorporate a hybridized advanced sine-cosine algorithm (ASCA) and advanced ant colony optimization (AACO) technique for optimal path search with…

199

Abstract

Purpose

This paper aims to incorporate a hybridized advanced sine-cosine algorithm (ASCA) and advanced ant colony optimization (AACO) technique for optimal path search with control over multiple mobile robots in static and dynamic unknown environments.

Design/methodology/approach

The controller for ASCA and AACO is designed and implemented through MATLAB simulation coupled with real-time experiments in various environments. Whenever the sensors detect obstacles, ASCA is applied to find their global best positions within the sensing range, following which AACO is activated to choose the next stand-point. This is how the robot travels to the specified target point.

Findings

Navigational analysis is carried out by implementing the technique developed here using single and multiple mobile robots. Its efficiency is authenticated through the comparison between simulation and experimental results. Further, the proposed technique is found to be more efficient when compared with existing methodologies. Significant improvements of about 10.21 per cent in path length are achieved along with better control over these.

Originality/value

Systematic presentation of the proposed technique attracts a wide readership among researchers where AI technique is the application criteria.

Details

Industrial Robot: the international journal of robotics research and application, vol. 47 no. 4
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 11 February 2019

Sanjay Kumar Behera, Dayal R. Parhi and Harish C. Das

With the development of research toward damage detection in structural elements, the use of artificial intelligent methods for crack detection plays a vital role in…

Abstract

Purpose

With the development of research toward damage detection in structural elements, the use of artificial intelligent methods for crack detection plays a vital role in solving the crack-related problems. The purpose of this paper is to establish a methodology that can detect and analyze crack development in a beam structure subjected to transverse free vibration.

Design/methodology/approach

Hybrid intelligent systems have acquired their own distinction as a potential problem-solving methodology adopted by researchers and scientists. It can be applied in many areas like science, technology, business and commerce. There have been the efforts by researchers in the recent past to combine the individual artificial intelligent techniques in parallel to generate optimal solutions for the problems. So it is an innovative effort to develop a strong computationally intelligent hybrid system based on different combinations of available artificial intelligence (AI) techniques.

Findings

In the present research, an integration of different AI techniques has been tested for accuracy. Theoretical, numerical and experimental investigations have been carried out using a fix-hinge aluminum beam of specified dimension in the presence and absence of cracks. The paper also gives an insight into the comparison of relative crack locations and crack depths obtained from numerical and experimental results with that of the results of the hybrid intelligent model and found to be in good agreement.

Originality/value

The paper covers the work to verify the accuracy of hybrid controllers in a fix-hinge beam which is very rare to find in the available literature. To overcome the limitations of standalone AI techniques, a hybrid methodology has been adopted. The output results for crack location and crack depth have been compared with experimental results, and the deviation of results is found to be within the satisfactory limit.

Details

International Journal of Structural Integrity, vol. 10 no. 2
Type: Research Article
ISSN: 1757-9864

Keywords

Article
Publication date: 16 October 2018

Dayal R. Parhi and Animesh Chhotray

This paper aims to generate an obstacle free real time optimal path in a cluttered environment for a two-wheeled mobile robot (TWMR).

Abstract

Purpose

This paper aims to generate an obstacle free real time optimal path in a cluttered environment for a two-wheeled mobile robot (TWMR).

Design/methodology/approach

This TWMR resembles an inverted pendulum having an intermediate body mounted on a robotic mobile platform with two wheels driven by two DC motors separately. In this article, a novel motion planning strategy named as DAYANI arc contour intelligent technique has been proposed for navigation of the two-wheeled self-balancing robot in a global environment populated by obstacles. The developed new path planning algorithm evaluates the best next feasible point of motion considering five weight functions from an arc contour depending upon five separate navigational parameters.

Findings

Authenticity of the proposed navigational algorithm has been demonstrated by computing the path length and time taken through a series of simulations and experimental verifications and the average percentage of error is found to be about 6%.

Practical implications

This robot dynamically stabilizes itself with taller configuration, can spin on the spot and rove along through obstacles with smaller footprints. This diversifies its areas of application to both indoor and outdoor environments especially with very narrow spaces, sharp turns and inclined surfaces where its multi-wheel counterparts feel difficult to perform.

Originality/value

A new obstacle avoidance and path planning algorithm through incremental step advancement by evaluating the best next feasible point of motion has been established and verified through both experiment and simulation.

Details

Industrial Robot: An International Journal, vol. 45 no. 5
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 4 March 2021

Abhishek Kumar Kashyap and Dayal R. Parhi

Humanoid robots have complicated dynamics, and they lack dynamic stability. Despite having similarities in kinematic structure, developing a humanoid robot with robust…

Abstract

Purpose

Humanoid robots have complicated dynamics, and they lack dynamic stability. Despite having similarities in kinematic structure, developing a humanoid robot with robust walking is quite difficult. In this paper, an attempt to produce a robust and expected walking gait is made by using an ALO (ant lion optimization) tuned linear inverted pendulum model plus flywheel (LIPM plus flywheel).

Design/methodology/approach

The LIPM plus flywheel provides the stabilized dynamic walking, which is further optimized by ALO during interaction with obstacles. It gives an ultimate turning angle, which makes the robot come closer to the obstacle and provide a turning angle that optimizes the travel length. This enhancement releases the constraint on the height of the COM (center of mass) and provides a larger stride. The framework of a sequential locomotion planer has been discussed to get the expected gait. The proposed method has been successfully tested on a simulated model and validated on the real NAO humanoid robot.

Findings

The convergence curve defends the selection of the proposed controller, and the deviation under 5% between simulation and experimental results in regards to travel length and travel time proves its robustness and efficacy. The trajectory of various joints obtained using the proposed controller is compared with the joint trajectory obtained using the default controller. The comparison shows the stable walking behavior generated by the proposed controller.

Originality/value

Humanoid robots are preferred over mobile robots because they can easily imitate the behaviors of humans and can result in higher output with higher efficiency for repetitive tasks. A controller has been developed using tuning the parameters of LIPM plus flywheel by the ALO approach and implementing it in a humanoid robot. Simulations and experiments have been performed, and joint angles for various joints are calculated and compared with the default controller. The tuned controller can be implemented in various other humanoid robots

Details

International Journal of Intelligent Unmanned Systems, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2049-6427

Keywords

Article
Publication date: 13 February 2017

B.K. Patle, Dayal R. Parhi, A. Jagadeesh and Sunil Kumar Kashyap

This paper aims to propose an optimized overview of firefly algorithm (FA) over physical-natural impression of fireflies and its application in mobile robot navigation…

Abstract

Purpose

This paper aims to propose an optimized overview of firefly algorithm (FA) over physical-natural impression of fireflies and its application in mobile robot navigation under the natural intelligence mechanism.

Design/methodology/approach

The brightness and luminosity are the decision variables in proposed study. The paper achieves the two major goals of robot navigation; first, the optimum path generation and, second, as an obstacle avoidance by co-in-centric sphere-based geometrical technique. This technique comprises the optimum path decision to objective function and constraints to paths and obstacles as the function of algebraic-geometry co-relation. Co-in-centric sphere is the proposed technique to correlate the constraints.

Findings

It is found that the present FA based on concentric sphere is suitable for efficient navigation of mobile robots at the level of optimum significance when compared with other approaches.

Originality/value

The paper introduces a novel approach to implement the FA for unknown and uncertain environment.

Details

World Journal of Engineering, vol. 14 no. 1
Type: Research Article
ISSN: 1708-5284

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…

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: 10 June 2019

Asita Kumar Rath, Dayal R. Parhi, Harish Chandra Das, Priyadarshi Biplab Kumar, Manoj Kumar Muni and Kitty Salony

Humanoids have become the center of attraction for many researchers dealing with robotics investigations by their ability to replace human efforts in critical…

Abstract

Purpose

Humanoids have become the center of attraction for many researchers dealing with robotics investigations by their ability to replace human efforts in critical interventions. As a result, navigation and path planning has emerged as one of the most promising area of research for humanoid models. In this paper, a fuzzy logic controller hybridized with genetic algorithm (GA) has been proposed for path planning of a humanoid robot to avoid obstacles present in a cluttered environment and reach the target location successfully. The paper aims to discuss these issues.

Design/methodology/approach

Here, sensor outputs for nearest obstacle distances and bearing angle of the humanoid are first fed as inputs to the fuzzy logic controller, and first turning angle (TA) is obtained as an intermediate output. In the second step, the first TA derived from the fuzzy logic controller is again supplied to the GA controller along with other inputs and second TA is obtained as the final output. The developed hybrid controller has been tested in a V-REP simulation platform, and the simulation results are verified in an experimental setup.

Findings

By implementation of the proposed hybrid controller, the humanoid has reached its defined target position successfully by avoiding the obstacles present in the arena both in simulation and experimental platforms. The results obtained from simulation and experimental platforms are compared in terms of path length and time taken with each other, and close agreements have been observed with minimal percentage of errors.

Originality/value

Humanoids are considered more efficient than their wheeled robotic forms by their ability to mimic human behavior. The current research deals with the development of a novel hybrid controller considering fuzzy logic and GA for navigational analysis of a humanoid robot. The developed control scheme has been tested in both simulation and real-time environments and proper agreements have been found between the results obtained from them. The proposed approach can also be applied to other humanoid forms and the technique can serve as a pioneer art in humanoid navigation.

Details

International Journal of Intelligent Unmanned Systems, vol. 7 no. 3
Type: Research Article
ISSN: 2049-6427

Keywords

Article
Publication date: 4 October 2021

Chittaranjan Paital, Saroj Kumar, Manoj Kumar Muni, Dayal R. Parhi and Prasant Ranjan Dhal

Smooth and autonomous navigation of mobile robot in a cluttered environment is the main purpose of proposed technique. That includes localization and path planning of…

Abstract

Purpose

Smooth and autonomous navigation of mobile robot in a cluttered environment is the main purpose of proposed technique. That includes localization and path planning of mobile robot. These are important aspects of the mobile robot during autonomous navigation in any workspace. Navigation of mobile robots includes reaching the target from the start point by avoiding obstacles in a static or dynamic environment. Several techniques have already been proposed by the researchers concerning navigational problems of the mobile robot still no one confirms the navigating path is optimal.

Design/methodology/approach

Therefore, the modified grey wolf optimization (GWO) controller is designed for autonomous navigation, which is one of the intelligent techniques for autonomous navigation of wheeled mobile robot (WMR). GWO is a nature-inspired algorithm, which mainly mimics the social hierarchy and hunting behavior of wolf in nature. It is modified to define the optimal positions and better control over the robot. The motion from the source to target in the highly cluttered environment by negotiating obstacles. The controller is authenticated by the approach of V-REP simulation software platform coupled with real-time experiment in the laboratory by using Khepera-III robot.

Findings

During experiments, it is observed that the proposed technique is much efficient in motion control and path planning as the robot reaches its target position without any collision during its movement. Further the simulation through V-REP and real-time experimental results are recorded and compared against each corresponding results, and it can be seen that the results have good agreement as the deviation in the results is approximately 5% which is an acceptable range of deviation in motion planning. Both the results such as path length and time taken to reach the target is recorded and shown in respective tables.

Originality/value

After literature survey, it may be said that most of the approach is implemented on either mathematical convergence or in mobile robot, but real-time experimental authentication is not obtained. With a lack of clear evidence regarding use of MGWO (modified grey wolf optimization) controller for navigation of mobile robots in both the environment, such as in simulation platform and real-time experimental platforms, this work would serve as a guiding link for use of similar approaches in other forms of robots.

Details

International Journal of Intelligent Unmanned Systems, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2049-6427

Keywords

Article
Publication date: 9 September 2021

Abhishek Kumar Kashyap and Dayal R. Parhi

This paper aims to outline and implement a novel hybrid controller in humanoid robots to map an optimal path. The hybrid controller is designed using the Owl search…

Abstract

Purpose

This paper aims to outline and implement a novel hybrid controller in humanoid robots to map an optimal path. The hybrid controller is designed using the Owl search algorithm (OSA) and Fuzzy logic.

Design/methodology/approach

The optimum steering angle (OS) is used to deal with the obstacle located in the workspace, which is the output of the hybrid OSA Fuzzy controller. It is obtained by feeding OSA's output, i.e. intermediate steering angle (IS), in fuzzy logic. It is obtained by supplying the distance of obstacles from all directions and target distance from the robot's present location.

Findings

The present research is based on the navigation of humanoid NAO in complicated workspaces. Therefore, various simulations are performed in a 3D simulator in different complicated workspaces. The validation of their outcomes is done using the various experiments in similar workspaces using the proposed controller. The comparison between their outcomes demonstrates an acceptable correlation. Ultimately, evaluating the proposed controller with another existing navigation approach indicates a significant improvement in performance.

Originality/value

A new framework is developed to guide humanoid NAO in complicated workspaces, which is hardly seen in the available literature. Inspection in simulation and experimental workspaces verifies the robustness of the designed navigational controller. Considering minimum error ranges and near collaboration, the findings from both frameworks are evaluated against each other in respect of specified navigational variables. Finally, concerning other present approaches, the designed controller is also examined, and major modifications in efficiency have been reported.

Details

Industrial Robot: the international journal of robotics research and application, vol. 49 no. 2
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 14 May 2019

Anish Pandey, Abhishek Kumar Kashyap, Dayal R. Parhi and B.K. Patle

This paper aims to design and implement the multiple adaptive neuro-fuzzy inference system (MANFIS) architecture-based sensor-actuator (motor) control technique for mobile…

Abstract

Purpose

This paper aims to design and implement the multiple adaptive neuro-fuzzy inference system (MANFIS) architecture-based sensor-actuator (motor) control technique for mobile robot navigation in different two-dimensional environments with the presence of static and moving obstacles.

Design/methodology/approach

The three infrared range sensors have been mounted on the front, left and right side of the robot, which reads the forward, left forward and right forward static and dynamic obstacles in the environment. This sensor data information is fed as inputs into the MANFIS architecture to generate appropriate speed control commands for right and left motors of the robot. In this study, we have taken one assumption for moving obstacle avoidance in different scenarios the speed of the mobile robot is at least greater than or equal to the speed of moving obstacles and goal.

Findings

Graphical simulations have designed through MATLAB and virtual robot experimentation platform (V-REP) software and experiments have been done on Arduino MEGA 2560 microcontroller-based mobile robot. Simulation and experimental studies demonstrate the effectiveness and efficiency of the proposed MANFIS architecture.

Originality/value

This paper designs and implements MANFIS architecture for mobile robot navigation between a static and moving obstacle in different simulation and experimental environments. Also, the authors have compared this developed architecture to the other navigational technique and found that our developed architecture provided better results in terms of path length in the same environment.

Details

World Journal of Engineering, vol. 16 no. 2
Type: Research Article
ISSN: 1708-5284

Keywords

1 – 10 of 15