Autonomous Vehicle Turning Control for Narrow-Area Coverage
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Solution Overview
Problem
Autonomous vehicles face challenges in efficiently navigating and covering working areas, particularly in narrow spaces and areas with obstacles, due to poor path planning, leading to reduced efficiency, increased mechanical wear, and shortened service life.
Innovation Solution
An autonomous vehicle with a central axis dividing it into left and right sides, equipped with a driving module, limit detecting module, and control module, which detects the location relationship with limits and makes rational turns to maintain a smaller distance from one side to the limit, allowing continuous movement and improved coverage efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the autonomous vehicle adopts random paths during moving and stops frequently to make turns, then it can navigate through the working scope, but it increases stopping times and reduces overall moving speed
Solution Approach 1:
The vehicle performs preliminary actions by detecting limits ahead of time and planning turn paths in advance. The control module predicts future positions and calculates optimal turn paths before the vehicle actually needs to turn, allowing smoother transitions and reducing stopping time.
Solution Approach 2:
The vehicle dynamically adjusts its moving speed and turn radius based on real-time position and limit detection. The control module continuously updates the turn path parameters to optimize the balance between maintaining coverage and minimizing stopping time, making the navigation adaptive rather than static.
2Adaptability or versatility
If the autonomous vehicle stops and makes random turns in narrow areas, then it can attempt to leave the area, but it increases the time needed to leave and may fail to leave
Solution Approach 1:
The control module continuously monitors the vehicle's position relative to limits and uses this feedback to adjust the turn path in real-time. By detecting whether the vehicle is in a narrow area and how close it is to limits, the system dynamically modifies the turn strategy to ensure successful exit while minimizing time spent.
Solution Approach 2:
The vehicle performs preliminary detection of narrow areas and calculates optimal escape paths before fully entering problematic situations. The control module anticipates potential trapping scenarios and prepares appropriate turn sequences in advance.
3Area of stationary object
If the autonomous vehicle frequently starts and stops in the whole working process, then it can cover the working area, but it reduces overall moving speed and increases mechanical wear
Solution Approach 1:
The vehicle maintains continuous motion by planning turn paths that minimize stopping. The control module calculates turn sequences that allow the vehicle to maintain momentum and reduces the frequency of complete stops, thereby preserving productivity while still achieving comprehensive area coverage.
Solution Approach 2:
The system dynamically optimizes the balance between coverage and speed by adjusting turn frequencies and paths based on the vehicle's current position, battery level, and mission progress. This dynamic optimization reduces unnecessary stops while ensuring complete coverage.
4Adaptability or versatility
If the autonomous vehicle adopts random turning paths, then it can navigate obstacles, but it fails to rationally judge the optimal turning direction
Solution Approach 1:
The control module performs preliminary calculations of multiple possible turn paths and evaluates them based on coverage efficiency and progress toward mission goals. By pre-calculating and comparing different turning options, the system makes informed decisions rather than random choices.
Solution Approach 2:
The system uses feedback from limit detection and position monitoring to continuously refine turn path selection. The control module evaluates the effectiveness of previous turns and adjusts future turn directions based on this feedback, improving direction judgment accuracy over time.
Data Source
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AI summary
A turning method is implemented in an autonomous vehicle having a central axis which divides the autonomous vehicle into left side and right side. In the method, the autonomous vehicle moves towards a limit; the autonomous vehicle monitors the location relationship of the vehicle with the limit; and the autonomous vehicle judges which side is closer to the limit when reaching a predetermined location relationship with the limit. The autonomous vehicle makes a turn and moves away from the limit, so that the distance from one side of the autonomous vehicle to the limit is always smaller than that from the other side to the limit. An autonomous vehicle and an autonomous working system are also disclosed.