Improved Intelligent Base Technique for Path and Solution in Robotic Using Prewill Edge Detection Paradigm
Downloads
The major contribution in this research paper is concerned with the development of a humanoid robot using edge detection technique which selects features of the principal parts of the object and eliminates parts that are not necessary. The developed prototype of the motorized robot shows that robots in real life exhibit some level of intelligence. In the design process, the model of a humanoid robot was developed first using the simulink library tools in Matlab/Simulink environment. This research paper has improved autonomous path finding robots by incorporating very powerful and well-structured program/codes that gives the robot the ability to predict and make smart decision lending to efficient execution of desired assignment (picking of dirt in the surrounding).Result shows that the developed robot has simplified the way No robot interacts with object thereby saving cost and energy. A motorized autonomous path finding robot was designed and constructed to demonstrate the working principle of robot. The motorized robot and the humanoid robot have the capability to detect obstacle along its part at 30cm away from the obstacle. When the robot is switched on, it initializes after which forward movement until it gets 30cm closer to an obstacle it then stops, reverse backwards and then change direction. When it moves 30cm close to another obstacle, it stops reverse backwards, then turns left or right to another direction, and will continue to behave that way until the power button is switched off.
Jinfa, C., (2015). An Intelligent Human-Tracking Robot Based-On Kinect Sensor. Graduate and Professional Studies of Texas A&M University
Karl, T., Anastasia, B. & Gholamreza, A. (2016). Edge information based object classification for NAO robots. Cogent Engineering (2016), 3: 1262571 http://dx.doi.org/10.1080/23311916.2016.1262571
Kheddar, A., Caron, S., Gergondet, P., Comport, A., Tanguy, A., Ott, C., Henze, B., Mesesan, G, Englsberger, J., Roa, M., Wieber, P., Chaumette, F., Splindler, F., Oriolo, G., Lanari, L., Escande, A., Chapplellet, K., Kanehiro, F., Rabate P.(2019)
Humanoid robots in aircraft Manufacturing IEEE Robotics and Automation Magazine, institute of Electrical and Electronics Engineers
Kumar, P., Mohapatra, S., Parhi, D. (2018) An intelligent navigation of humanoid NAO in the light of classical approach and computational intelligence https://doi.org/10.1002/cav.1858
Linert, J., & Kopacek, P., (2018). Humanoid robot Robotainment.www.sciencedirect.com
Liu Y(2015)., Wensing P., Orin D., Zheng Y. Dynamic walking in a humanoid robot based on a 3D actuated dual-SLIP model
Majid, K., Alexander, H., Ali, A., Moosavian, & Ludovic, R. (2017). A robust walking controller based on online step location and duration optimization for bipedal locomotion. www.researchgate.net/publications
Malavika, B., (2017). Biorobotic Locomotion: Biped Humanoid Walking using Optimal Control. School of Electrical and Computer Engineering Georgia Institute of Technology.
Milan, A., (2015). Modelling and control of walking robots.Electrical Engineering and Information Technology Branch of study: Control Engineering and Robotics Prague.
Pedro, P., (2019). An Omni-Directional Kick Engine for NAO Humanoid Robot.
https://scholarlyrepository.miami.edu/oa_theses
Poobathy D., Chezian M., (2017) An analysis on edge detection algorithms based on processing time one day nationa conference on green computing September 22nd 2017
Raffard, S.; Khoramshahi, M.; Burca, M.; Marin, L.; Bardy,B.; Billard, A.; Macioce. V.; Capdevielle (2016) Humanoid robots versus humans: How is emotional valence of facial expressions recognized by individuals with schizophrenia www.elsevier.com
Retto, J. (2017) Sophia, First citizen robot of the world National university of SAN marcos
Simon, K., (2017). Design for 3d Agility And Virtual Compliance Using Proprioceptive Force Control In Dynamic Legged Robots. Robotics institute, school of computer science at Carnegie mellon university
Tomas G. (2009) Artificial Visionin the Nao Humanoid Robot Department of Computer Science and Mathematics university of Rovira
Valez, K. (2019) Self Learning Guide Bioloid Humanoid robot Assembly with Elements of Augmented Reality to support using a 3D model technique and equally created an augmented reality International Conference on Human-Computer Interaction
Widodo, B., Anggita, D., Cahyanib, P., Rumondorb C.& Derwin, S. (2017). Intelligent Humanoid Robot With Natural Interaction for Education and Entertainment. www.elsevier.com Procedia Computer Science 116 (2017) 564–570
Wisskirchen, G. Biacabe, B., Muntz, A. Niehaus, G. Soler, G. 2017, Artificial intelligence and robotics and their impact on the workplace IBA Global Employment Institute
Xinyang, J., Xuechao C., Zhangguo, Y., Weimin, Z. & Libo M. (2018).
Motion Planning for Bipedal Robot to Perform Jump Maneuver. Multidisciplinary Digital Publishing Institute
ZHOU, Y (2011) Fuzzy Omnidirectional Walking Controller for the Humanoid Soccer RobotSchool of Information Science and Engineering, Southeast UniversityNanjing 210096, China
Xiong, Y., Haotian , H., Toshio F., & Yajing, S., (2017). State of the Art: Bipedal Robots for Lower Limb Rehabilitation .Multidisciplinary Digital Publishing Institute
Zahra, K., (2017). Multibody Dynamics Model of a Full Human Body for Simulating Walking. Purdue University Indianapolis, Indiana
