A New Cloud Robots Training Method Using Cooperative Learning

Du, Guanglong; Wang, Zhiyao; Li, Zhelin

doi:10.1109/access.2020.2966226

Cited by 4 publications

(2 citation statements)

References 19 publications

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“…Despite the current situation of community quarantine, the program was initiated effectively through online platforms. It is manifested that when the generalized methodology used in a particular robotics training it enables a more structured process in learning the required goal of the activity for potential better results (Nurbekova, et al, 2018;Du, Wang, Li, 2020).…”

Section: Findings and Discussionmentioning

confidence: 99%

Assessing the Efficacy of RoboTeach Extension Project on Public School Teachers

Gonzales

Andal

CHING

et al. 2021

IJEMDS

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The integration of robotics in the education was one of the aspirations of the K-12 institution in the Philippines. The RoboTeach Extension Project was established to address the challenges associated with the implementation of robotics in K-12 education. This study explores the teachers' perception of the efficacy in the implementation of the project which focused on training the Department of Education (DepEd) teachers in San Pablo City Laguna, Philippines on the basic concepts and applications of robotics and automation. The topics and learning activities covered during the ten-day training were based on the self-assessment survey results on the level of knowledge of teachers. The study used a descriptive method of research using a quantitative approach and adopted the LSPU Extension Services Evaluation Survey Questionnaire to determine the respondents' perception of the level of project efficacy. The data were obtained from twenty-five DepEd teachers and analyzed using descriptive statistics such as frequency count, per cent, weighted mean and ANOVA. The respondents were highly satisfied with meeting expectations to attain objectives, training and workshop contents, learning activities, methodologies, instructional materials used, resource person and trainers, training management team, and training management team and training facilities and services. Further, there was no significant difference among their level of satisfaction from day 1 to 5 of the training sessions. Respondents viewed the training as very successful, as evident from the consultation and culminating activity. Thus, the sustainability on the implementation of the project was highly recommended.

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Section: Findings and Discussionmentioning

confidence: 99%

Assessing the Efficacy of RoboTeach Extension Project on Public School Teachers

Gonzales

Andal

CHING

et al. 2021

IJEMDS

View full text Add to dashboard Cite

show abstract

“…Except for learning from robotic simulation, some researchers studied imitation learning or programming from demonstration technology for cloud-based applications, such as Song et al (2017) studied cloud-based robot learning for trajectory modification and certification by using two robots (a dual-arm home service robot and a TM5 robot). Du et al (2020) used imitated learning for robotic learning based on incorporated incremental learning and meta learning. But the generalized trajectories are not explainable and are hard to prove convergence and stability.…”

Section: Introductionmentioning

confidence: 99%

Dynamic movement primitives based cloud robotic skill learning for point and non-point obstacle avoidance

Wang

2021

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Purpose Dynamic movement primitives (DMPs) is a general robotic skill learning from demonstration method, but it is usually used for single robotic manipulation. For cloud-based robotic skill learning, the authors consider trajectories/skills changed by the environment, rebuild the DMPs model and propose a new DMPs-based skill learning framework removing the influence of the changing environment. Design/methodology/approach The authors proposed methods for two obstacle avoidance scenes: point obstacle and non-point obstacle. For the case with point obstacles, an accelerating term is added to the original DMPs function. The unknown parameters in this term are estimated by interactive identification and fitting step of the forcing function. Then a pure skill despising the influence of obstacles is achieved. Using identified parameters, the skill can be applied to new tasks with obstacles. For the non-point obstacle case, a space matching method is proposed by building a matching function from the universal space without obstacle to the space condensed by obstacles. Then the original trajectory will change along with transformation of the space to get a general trajectory for the new environment. Findings The proposed two methods are certified by two experiments, one of which is taken based on Omni joystick to record operator’s manipulation motions. Results show that the learned skills allow robots to execute tasks such as autonomous assembling in a new environment. Originality/value This is a new innovation for DMPs-based cloud robotic skill learning from multi-scene tasks and generalizing new skills following the changes of the environment.

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Application of Machine Learning Algorithms in Agriculture: An Analysis

Jain

Choudhary

2021

Studies in Autonomic, Data-Driven and Industrial Computing

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A New Cloud Robots Training Method Using Cooperative Learning

Cited by 4 publications

References 19 publications

Assessing the Efficacy of RoboTeach Extension Project on Public School Teachers

Assessing the Efficacy of RoboTeach Extension Project on Public School Teachers

Dynamic movement primitives based cloud robotic skill learning for point and non-point obstacle avoidance

Application of Machine Learning Algorithms in Agriculture: An Analysis

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