Postgraduate Seminar by Hafiq
Hafiq Anas presented his latest results on "Comparison of Deep Q Learning, Q Learning and SARSA Reinforced Learning for Robot Local Navigation"
On 8th December 2021, the School of Digital Science organised a postgraduate seminar talk:
Comparison of Deep Q Learning, Q Learning and SARSA Reinforced Learning for Robot Local Navigation by Hafiq Anas
Abstract
This talk presents a performance comparison of mobile robot obstacle avoidance between using Deep Reinforcement Learning (DRL) and two classical Reinforcement Learning (RL). For the DRL based method, Deep Q Learning (DQN) algorithm was used whereas for the RL based method, Q Learning and Sarsa algorithms were used. In our experiments, we have used the extended OpenAI Gym ToolKit to compare the performances of DQN, Q Learning, and Sarsa algorithms in both simulated and real world environments. Turtlebot3 Burger was used as the mobile robot hardware to evaluate the performance of the RL models in the real world environment. The average rewards, episode steps, and rate of successful navigation were used to compare the performance of the navigation ability of the RL agents. Based on the simulated and real world results, DQN has performed significantly better than both Q Learning and Sarsa . It has achieved 100% success rates during the simulated and real world tests.
Speaker bio:
Hafiq Anas received his BSc in Computer Science from Universiti Brunei Darussalam in 2019. He is now an MSc student in the School of Digital Science, UBD. He has worked as a Research Assistant at UBD involving the implementation of Automatic Facial Expression Recognition system and experimenting with such a system against numerous controlled and wild datasets. His research interests include robot navigation and machine learning in interdisciplinary fields.
He is currently under the supervision of Dr Wee Hong Ong and Dr Owais Malik.
This current work has been accepted in RiTA2021. Well done, Hafiq!
To date, Hafiq has published the following papers:
arXiv:2108.12571: An implementation of ROS Autonomous Navigation on Parallax Eddie platform
Authors: Hafiq Anas, Wee Hong Ong
Abstract: This paper presents an implementation of autonomous navigation functionality based on Robot Operating System (ROS) on a wheeled differential drive mobile platform called Eddie robot. ROS is a framework that contains many reusable software stacks as well as visualization and debugging tools that provides an ideal environment for any robotic project development. The main contribution of this paper i… ▽ More
arXiv:2010.01301: Deep Convolutional Neural Network Based Facial Expression Recognition in the Wild
Authors: Hafiq Anas, Bacha Rehman, Wee Hong Ong
Abstract: This paper describes the proposed methodology, data used and the results of our participation in the ChallengeTrack 2 (Expr Challenge Track) of the Affective Behavior Analysis in-the-wild (ABAW) Competition 2020. In this competition, we have used a proposed deep convolutional neural network (CNN) model to perform automatic facial expression recognition (AFER) on the given dataset. Our proposed mod…
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