Autonomous Lawn Mower Navigation Under Localization Uncertainty
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Solution Overview
Problem
Existing autonomous work equipment, such as lawn mowers, face challenges in navigating and controlling their movements within work areas due to uncertainties in localization and sensor data, leading to potential collisions and inefficient path planning.
Innovation Solution
The proposed procedure involves evaluating probability characteristics of the autonomous work equipment's conditions, including localization uncertainty, to determine a secure and collision-free movement path. This is achieved by combining work area data with sensor data to create a localization card, which estimates the probability of the equipment's position within the work area. Additionally, the procedure discretizes probability characteristics and evaluates them in uncertainty levels to optimize movement paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional navigation methods are used without probability evaluation, then the control system is simpler, but the localization uncertainty increases leading to potential collisions
Solution Approach 1:
The system performs preliminary evaluation of probability characteristics and localization uncertainty before determining the movement path. By assessing collision probabilities in advance and planning paths that account for uncertainty, the system prevents collisions before they occur rather than reacting to them
Solution Approach 2:
The system continuously updates probability characteristics and localization uncertainty based on sensor data and movement execution. This feedback loop allows the control system to adapt to actual conditions and maintain reliable collision-free operation
2Measurement precision
If probability characteristics are evaluated in detail, then the movement path accuracy improves, but the computational time increases
Solution Approach 1:
The system evaluates probability characteristics at discrete uncertainty levels rather than continuously across all possible states. By focusing computation on the most relevant probability ranges and discretizing the state space, the system achieves sufficient localization precision without exhaustive computational analysis
3Reliability
If the working area is completely covered with high probability, then the work quality improves, but the movement path length increases
Solution Approach 1:
The system dynamically adjusts the movement path based on evaluated probability characteristics and localization uncertainty. Rather than following a fixed predetermined path, the autonomous device adapts its trajectory in real-time to maintain coverage reliability while minimizing unnecessary travel distance
Data Source
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AI summary
The invention relates to a method for controlling, in particular navigating, at least one autonomous working device, in particular an autonomous lawn mower, within a working region (14), wherein in at least one method step (16) working region data, in particular map data of the working region, are captured and in at least one method step (18) sensor data of the autonomous working device are captured. According to the invention, in at least one method step (20) at least one probability characteristic of possible states of the autonomous working device within the working region (14), which probability characteristic describes at least one locating uncertainty, in particular a sensing and/or movement uncertainty, of the autonomous working device, is evaluated, in particular in order to determine at least one motion path (22) of the autonomous working device, which motion path at least substantially completely covers the working region (14).