Learning to Explore Indoor Environments using Autonomous Micro Aerial Vehicles

Keyphrases

• Indoor Environment 100%
• Weight Constraint 100%
• Autonomous Micro Aerial Vehicles 100%
• Power Constraint 100%
• Deep Learning 66%
• Deep Reinforcement Learning (deep RL) 66%
• Learning-based 33%
• State-of-the-art Techniques 33%
• Tightly Coupled 33%
• Exploratory Framework 33%
• Planners 33%
• Occupancy 33%
• Unknown Indoor Environment 33%
• Two-module 33%
• Unknown Environment 33%
• Mission Time 33%
• Autonomous Aerial Robots 33%
• Indoor Map 33%
• Trajectory Length 33%
• Unseen Environments 33%
• Neural Processor 33%

Computer Science

• Power Constraint 100%
• Deep Reinforcement Learning 66%
• Deep Learning Method 66%
• Robot 33%
• Trajectory Length 33%