Autonomous Machine Return Navigation for Energy-Aware Charging
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Solution Overview
Problem
Existing autonomous machines waste energy and battery life by randomly searching for boundary wires to find their base station for charging.
Innovation Solution
An autonomous machine equipped with a navigation system that predicts battery energy needs and identifies an efficient path to return to a base station or destination, using a battery management system to determine remaining energy and an estimated travel energy threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If autonomous machines randomly search for boundary wires to find base station, then they can locate charging position, but energy and battery life are wasted
Solution Approach 1:
The patent applies preliminary action by implementing a navigation system that pre-calculates optimal paths to the base station using map data and current position information. Instead of randomly searching for boundary wires, the system proactively determines the most energy-efficient route in advance, significantly reducing unnecessary energy consumption while maintaining reliable charging location accuracy
Solution Approach 2:
The patent replaces the mechanical/random boundary wire following approach with an intelligent navigation system that uses computational algorithms, map data, and position information to calculate optimal paths. This substitution of mechanical search behavior with intelligent computational navigation eliminates random energy-wasting movements while ensuring accurate base station location
2Reliability
If autonomous machines randomly search for boundary wires, then they can find base station, but time is wasted
Solution Approach 1:
The navigation system performs preliminary path planning by pre-calculating optimal routes to the base station using stored map data and current position. This advance calculation eliminates time-wasting random searches and boundary wire following, directing the machine efficiently along the shortest or most suitable path while ensuring accurate arrival at the charging location
3Device complexity
If autonomous machines use boundary wire following method, then navigation is simple, but energy efficiency is poor
Solution Approach 1:
The patent replaces the simple but energy-inefficient boundary wire following mechanism with an intelligent navigation system that uses computational path optimization. The navigation system processes map data, calculates energy consumption for different routes, and selects optimal paths, achieving superior energy efficiency through intelligent computation rather than mechanical wire following
Solution Approach 2:
The patent applies parameter changes by dynamically evaluating multiple path options based on energy consumption parameters, distance, and terrain characteristics. The navigation system calculates and compares different route parameters to determine the most energy-efficient path, transforming the navigation approach from fixed boundary wire following to flexible parameter-based optimization
Data Source
AI summary
An autonomous machine may be returned to a base station for charging based on remaining battery energy and an estimated travel energy threshold. The estimated travel energy threshold may be determined based on a direct and obstacle-free route from the machine's current position to the base station and an estimated energy consumed per unit distance, which may be updated. The remaining battery energy may be calculated using a battery management system.