Sentiment Analysis of Nepali COVID19 Tweets Using NB, SVM AND LSTM
Volume-3 | Issue-3
Deniable Authentication Encryption for Privacy Protection using Blockchain
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Blockchain-Enabled Federated Learning on Kubernetes for Air Quality Prediction Applications
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Smart Fashion: A Review of AI Applications in Virtual Try-On & Fashion Synthesis
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QoS-aware Virtual Machine (VM) for Optimal Resource Utilization and Energy Conservation
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Fusion based Feature Extraction Analysis of ECG Signal Interpretation - A Systematic Approach
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Multi-scale CNN Approach for Accurate Detection of Underwater Static Fish Image
Volume-3 | Issue-3
Real Time Anomaly Detection Techniques Using PySpark Frame Work
Volume-2 | Issue-1
Deniable Authentication Encryption for Privacy Protection using Blockchain
Volume-3 | Issue-3
Smart Fashion: A Review of AI Applications in Virtual Try-On & Fashion Synthesis
Volume-3 | Issue-4
Sentiment Analysis of Nepali COVID19 Tweets Using NB, SVM AND LSTM
Volume-3 | Issue-3
Audio Tagging Using CNN Based Audio Neural Networks for Massive Data Processing
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Frontiers of AI beyond 2030: Novel Perspectives
Volume-4 | Issue-4
Smart Medical Nursing Care Unit based on Internet of Things for Emergency Healthcare
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Early Stage Detection of Crack in Glasses by Hybrid CNN Transformation Approach
Volume-3 | Issue-4
ARTIFICIAL INTELLIGENCE APPLICATION IN SMART WAREHOUSING ENVIRONMENT FOR AUTOMATED LOGISTICS
Volume-1 | Issue-2
Deep Convolution Neural Network Model for Credit-Card Fraud Detection and Alert
Volume-3 | Issue-2
Volume - 4 | Issue - 3 | september 2022
Published
19 August, 2022
Reinforcement learning is a well-proven and powerful algorithm for robotic arm manipulation. There are various applications of this in healthcare, such as instrument assisted surgery and other medical interventions where surgeons cannot find the target successfully. Reinforcement learning is an area of machine learning and artificial intelligence that studies how an agent should take actions in an environment so as to maximize its total expected reward over time. It does this by trying different ways through trial-and-error, hoping to be rewarded for the results it achieves. The focus of this paper is to use a deep reinforcement learning neural network to map the raw pixels from a camera to the robot arm control commands for object manipulation.
KeywordsDeep reinforcement learning robot arm gazebo deep learning artificial intelligence
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