Energy-Aware Planning for Delivery Tasks Executed by Legged Robots

Legged robots can significantly increase human productivity by performing delivery tasks. Legged robots cannot be tethered to power sources when operating in large outdoor environments. If a robot runs out of energy while executing a task, it will require human intervention, resulting in delays. On the other hand, frequent battery recharging or replacement could also lead to significant delays in task completion. This paper presents an energy-aware hierarchical planning approach that accounts for energy consumption and integrates appropriate battery replacement strategies to ensure that tasks are completed efficiently. Our algorithm generates graph search instances for varying battery replacement actions, the option to split the payload into smaller portions, and reducing speed in the first level, while running graph search to determine the optimal plan that minimizes the time to complete the delivery task. We illustrate the effectiveness of our planning approach on a terrain with varying slopes and delivery tasks with different requirements.