Autonomous Robot Recharging Using Detected Natural Energy Sources
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Solution Overview
Problem
Current microbots face challenges in maintaining sufficient power to perform tasks due to limited power supply capacity, which restricts their ability to perform multiple tasks effectively.
Innovation Solution
The system uses satellite image data and machine learning models to locate potential energy sources, such as citrus fruits, and recharge microbot batteries by inserting electrodes into these sources, ensuring efficient power management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Duration of action of moving object
If microbots are equipped with larger batteries to extend operational capacity, then duration of action is improved, but weight and volume increase
Solution Approach 1:
The microbot autonomously locates energy sources using satellite data and machine learning models, navigates to them, and recharges its battery by inserting electrodes into the energy source. This self-service capability eliminates the need for larger batteries, as the robot can replenish its power supply independently during operation.
2Duration of action of moving object
If microbots are equipped with larger batteries to extend operational capacity, then duration of action is improved, but device complexity increases
Solution Approach 1:
The system integrates satellite data processing, machine learning-based energy source location, autonomous navigation, and battery recharging into a unified self-service framework. The robot automatically manages the entire power replenishment process without human intervention, reducing the complexity of manual power management while extending operational capacity.
Solution Approach 2:
The system pre-processes satellite data and uses machine learning models to identify potential energy sources before the microbot reaches them. This preliminary action allows the robot to navigate directly to known energy sources, simplifying the power management system by reducing real-time decision-making complexity.
3Device complexity
If microbots rely on limited onboard power supply, then device complexity is reduced, but productivity decreases
Solution Approach 1:
The microbot autonomously manages its power supply by locating energy sources using satellite data and machine learning, navigating to them, and recharging its battery. This self-service capability maintains simple device architecture while significantly enhancing productivity, as the robot can perform multiple tasks across extended operational periods without human intervention.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables microbots to autonomously locate and recharge their batteries, extending their operational capacity and allowing them to perform a wider range of tasks without the need for human intervention.
Implementation Method 1
instructing the robot to insert a pair of electrodes into the suitable energy source to generate an electrical current to charge a battery of the robot
Data Source
AI summary
An embodiment establishes a potential energy source database based at least in part on sensor data received from a satellite, wherein the potential energy source database comprises coordinate data representative of a plurality of potential energy source locations. The embodiment instructs a robot to travel to a potential energy source location of the plurality of potential energy source locations. The embodiment scans the potential energy source location for a potential energy source. The embodiment detects the potential energy source in the potential energy source location. The embodiment evaluates whether the potential energy source meets a predetermined suitability criteria. The embodiment classifies the potential energy source as a suitable energy source. The embodiment instructs the robot to insert a pair of electrodes into the suitable energy source to generate an electrical current to charge a battery of the robot.