A Sample-Efficiency Comparison Between Evolutionary Algorithms and Deep Reinforcement Learning for Path Planning in an Environmental Patrolling Mission.
Samuel Yanes LuisFederico Peralta SamaniegoDaniel Gutiérrez-ReinaSergio L. Toral MarínPublished in: CEC (2021)
Keyphrases
- path planning
- evolutionary algorithm
- multi robot
- reinforcement learning
- mobile robot
- search and rescue
- unmanned aerial vehicles
- path planning algorithm
- dynamic environments
- collision avoidance
- path planner
- multi agent
- dynamic and uncertain environments
- optimal path
- optimization problems
- aerial vehicles
- robot path planning
- obstacle avoidance
- differential evolution
- genetic algorithm
- potential field
- autonomous navigation
- trajectory planning
- motion planning
- path finding
- indoor environments
- degrees of freedom
- multiple robots
- multi robot systems
- real robot
- state space
- collision free
- neural network
- autonomous vehicles
- navigation tasks
- simulated annealing
- search algorithm