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Deep Reinforcement Learning for Spatial Motion Planning in 3D Urban Environments
Oren Gal
, Yerach Doytsher
Research output
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Article
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peer-review
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Dive into the research topics of 'Deep Reinforcement Learning for Spatial Motion Planning in 3D Urban Environments'. Together they form a unique fingerprint.
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Keyphrases
3D Planning
25%
3D Visibility
25%
Aerial Vehicle
25%
Deep Reinforcement Learning (deep RL)
100%
Deep Reinforcement Learning Algorithm
25%
Dynamic Model
25%
Environment Constraints
25%
Motion Planner
25%
Motion Planning Problem
25%
Motion Primitives
25%
Obstacle Avoidance
25%
Planners
50%
Reinforcement Learning Approach
25%
Reward Function
25%
Spatial Analysis
25%
Spatial Motion
25%
Spatial Motion Planning
100%
Time-optimal
25%
UAV
25%
Urban Environment
100%
Value Function
25%
Visibility Analysis
50%
Visibility Constraints
25%
Computer Science
Deep Reinforcement Learning
100%
Function Value
20%
Learning Approach
20%
Motion Planning
100%
Obstacle Avoidance
20%
Reinforcement Learning
20%
Unmanned Aerial Vehicle
20%
Urban Environment
100%