Background
With the widespread application of robots in various fields, ensuring long-term operation through "energy efficiency" has become the greatest challenge for practical deployment. Mobile robots, constrained by their own battery capacities, easily face the bottleneck of premature power depletion when executing continuous communication and sensing tasks. Traditional operational mechanisms fail to effectively identify redundant power-consuming links, often leading to unnecessary power consumption.
Research Objectives
The core objective is to "maximize the overall lifetime of the robotic network." This project aims to significantly reduce the power consumption of onboard equipment through intelligent communication and resource-saving designs, achieving optimal, seamless power saving without affecting the robot's existing movement paths and basic task quality.
Methods
We will develop an intelligent energy-saving algorithm by analyzing the power status of different devices in the network in real-time. The system dynamically adjusts the sleep and wake-up times of robots, reducing invalid standby power consumption. Additionally, a task offloading mechanism is established, allowing low-battery mobile robots to hand over high-power communication or sensing tasks to nearby fully-powered fixed devices, achieving a collective energy-saving effect.
Innovation
Breaking the traditional power-consumption model where individual devices operate independently, this project pioneers a resource allocation framework based on the concept of "collective collaborative power saving." The system can automatically transfer and balance the power-consuming burden based on the actual environment, achieving true system-level energy savings, rather than being limited only to the power optimization of single robot hardware.
Expected Outcomes
It is expected to reduce the overall energy consumption of the Robotic IoT and substantially extend the task execution time of battery-powered devices. This energy-saving framework will provide strong and stable endurance guarantees for future large-scale robot system deployments, drastically reducing the operational and maintenance costs caused by frequent charging or battery replacement.