FOLD: Fog-dew infrastructure-aided optimal workload distribution for cloud robotic operations
In our fast-paced, technology-driven world, multi-robot systems have emerged as crucial
solutions to tackle contemporary challenges, from industrial automation to disaster …
solutions to tackle contemporary challenges, from industrial automation to disaster …
A two-stage reinforcement learning-based approach for multi-entity task allocation
Task allocation is a key combinatorial optimization problem, crucial for modern applications
such as multi-robot cooperation and resource scheduling. Decision makers must allocate …
such as multi-robot cooperation and resource scheduling. Decision makers must allocate …
Reinforcement learning-driven dynamic obstacle avoidance for mobile robot trajectory tracking
In this work, we propose a trajectory tracking method based on optimized Q-Learning (QL),
which has real-time obstacle avoidance capability, for controlling wheeled mobile robots in …
which has real-time obstacle avoidance capability, for controlling wheeled mobile robots in …