Designing an Algorithm for Bioloid Humanoid Navigating in its Indoor Environment

León, J.; Jayakumar, Varadharajan

doi:10.5923/j.jmea.20120203.01

Cited by 6 publications

(2 citation statements)

References 79 publications

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“…Akhtaruzzaman et al 22 have emphasized the implementation of a navigation approach for mobile robots in an indoor environment for optimized walking, turning and obstacle avoidance. Clever and Mombaur 23 have emphasized a walking transfer idea rooted in an inverse optimal approach methodology for the alteration of human movement to a humanoid robot.…”

Section: Introductionmentioning

confidence: 99%

Route outlining of humanoid robot on flat surface using MFO aided artificial potential field approach

Kashyap

Parhi

Kumar

2021

Proceedings of the Institution of Mechanical Engineers, Part B:

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Humanoid robots, with their overall resemblance to a human body, is modeled for flawless interaction with human-made tools or the environment. In this study, navigation of humanoid robot using hybrid Artificial potential field (APF) and Moth flame optimization (MFO) approach have been performed. The hybrid approach provides the final turning angle (FTA), which is optimum to avoid collision with the hindrances. APF utilizes a negative potential field and a positive potential field to find the location of obstacles and target, respectively. The navigation starts towards the target; when the robot interacts with the obstacle, APF provides an intermediate angle (IA). The IA, along with the position of the obstacle, is fed into MFO as an input. This technique provides the FTA (optimum) to avoid collisions and guide a robot to the target. It is implemented in a single humanoid system and a multi-humanoid system. The presence of multiple humanoids can create the chance of inter-collision. It is dismissed by employing a dining philosopher controller to the proposed technique. Simulations and experiments are accomplished on simulated and real humanoid NAO. The coherency in the behavior of the results evaluated by the simulations and real-time experiments demonstrates the efficiency of the proposed AI technique. Comparisons are performed with a previously used method to validate the robustness of the technique.

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Section: Introductionmentioning

confidence: 99%

Route outlining of humanoid robot on flat surface using MFO aided artificial potential field approach

Kashyap

Parhi

Kumar

2021

Proceedings of the Institution of Mechanical Engineers, Part B:

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“…Akhtaruzzaman et al proposed a navigational algorithm for navigation of humanoid robot in an indoor environment. The developed algorithm has the characteristics of gait like walking, turning, obstacle avoidance phenomenon to perform the task . Brooks et al designed a GODZILLA algorithm for humanoid robot motion planning in an unknown environment.…”

Section: Introductionmentioning

confidence: 99%

Implementation of grey wolf optimization controller for multiple humanoid navigation

Muni

Parhi

Kumar

2020

Computer Animation & Virtual

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In this paper, grey wolf optimization controller (GWOC) is considered as a multiobjective technique for multiple humanoid navigations. Upon activation of GWOC, the humanoids mimic the group hunting behavior of grey wolves and navigate toward the target in a collision-free manner in presence of both static and dynamic hurdles. The wolves in the pack will either diverge for searching prey or converge together for attacking the prey following the best search agent (Leader Alpha). GWOC has the ability to keep the humanoid free from being trapped in local minima whereas it facilitates it to head toward global minima. GWOC provides better results as compared to other intelligent techniques because of its five characteristics that include safe boundary, protection, following, hunting, and caring. Both simulation and experimental navigation in laboratory conditions for single as well as for multiple humanoid NAOs have been carried out. From the results of simulation and experimental data, it is confirmed that GWOC provides global minima for humanoid robots in complex environments with different shaped obstacles. A Petri-net controller is considered while navigating multiple humanoids, as during multiple humanoid navigations, one humanoid robot acts as a dynamic obstacle to other humanoids. K E Y W O R D SGWOC, NAO humanoid, navigation, petri-net model INTRODUCTIONLot of research works have been performed for path navigation of mobile robots, biped robots, and industrial robots by using both classical and artificial intelligent techniques. But there is still some improvement needed to avoid the trapping of robots in local minima. Today, the main challenging task for researchers is the path navigation of humanoids having multidegrees of freedom by using computational methods. Though several researchers are working on it, still it is in virtue to obtain the best intelligent method for effective and efficient navigation. For this purpose, grey wolf optimization controller (GWOC) is considered. The humanoid NAO considered for this research work is developed by ALDEBARAN robotics France, which is having 25 degrees of freedom. 1 There are sensors for detecting the obstacles, cameras to take the images of hurdles, motors, actuators, and batteries to perform the predefined tasks. The obstacle distances and shape of the obstacles are detected by inbuilt ultrasonic sensors and camera mount on the head. The programmed GWOC activates when NAO finds any obstacle in its path while heading toward target. Several researchers have worked toward the navigation of different kinds of robots using many intelligent techniques as path navigation of robots plays a Comp Anim Virtual Worlds. 2020;31:e1919. wileyonlinelibrary.com/journal/cav

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Quasi-inverse pendulum model of 12 DoF bipedal walking

Akhtaruzzaman

Shafie

Khan

2017

Int. J. Autom. Comput.

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Designing an Algorithm for Bioloid Humanoid Navigating in its Indoor Environment

Cited by 6 publications

References 79 publications

Route outlining of humanoid robot on flat surface using MFO aided artificial potential field approach

Route outlining of humanoid robot on flat surface using MFO aided artificial potential field approach

Implementation of grey wolf optimization controller for multiple humanoid navigation

Quasi-inverse pendulum model of 12 DoF bipedal walking

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