Smart Mower Visual-Inertial SLAM for Accurate Navigation
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Solution Overview
Problem
Existing smart mowers face challenges with low positioning accuracy and lack of environmental understanding, leading to inefficient navigation and obstacle avoidance, particularly in complex environments.
Innovation Solution
Integration of a camera for image data collection, an IMU for pose detection, and a processor for simultaneous localization and mapping (SLAM) to enhance positioning accuracy and environmental understanding, with optional features for distinguishing grassland and obstacles, and using visual-inertial fusion for improved navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS and boundary line signal with inertial measurement unit (IMU) are used for positioning, then the system cost is reduced, but positioning accuracy deteriorates
Solution Approach 1:
The patent combines multiple positioning technologies (satellite positioning, visual positioning, and inertial measurement) into a unified fusion positioning system. The processor integrates data from GPS modules, cameras, and IMU sensors to achieve high-accuracy positioning without relying solely on expensive RTK or UWB solutions, thereby resolving the contradiction between positioning accuracy and system complexity.
Solution Approach 2:
The positioning system is designed to support multiple positioning modes (satellite-based, vision-based, and inertial-based) that can be selectively activated depending on environmental conditions and accuracy requirements. This multi-functional approach allows the system to maintain high positioning accuracy across diverse scenarios while managing system complexity through conditional activation of different subsystems.
2Productivity
If simple positioning solutions are used, then hardware cost is reduced, but navigation and path planning efficiency deteriorates
Solution Approach 1:
The system continuously receives feedback from multiple sensors (GPS, camera, IMU) and dynamically adjusts the positioning and navigation strategy based on real-time accuracy assessments. When positioning accuracy falls below thresholds required for effective path planning, the system activates additional sensing modes or adjusts navigation parameters, ensuring navigation efficiency is maintained despite using cost-effective hardware.
3Adaptability or versatility
If autonomous mowing is implemented without environmental understanding, then automation is achieved, but ability to cope with complex situations deteriorates
Solution Approach 1:
The system performs preliminary environmental scanning and mapping using the camera and processor before autonomous mowing begins. It identifies obstacles, terrain features, and boundary lines in advance, building an environmental model that guides subsequent autonomous navigation. This preliminary action enables the mower to adapt to complex environments while maintaining full automation during the mowing operation.
Data Source
AI summary
A smart mower includes a camera for collecting image data of the environment around the smart mower; an inertial measurement unit (IMU) for detecting pose data of the smart mower; a memory at least used for storing an application program for controlling the smart mower to work or travel; and a processor for calling the application program, fusing the image data collected by the camera and the pose data acquired by the IMU, performing simultaneous localization and mapping (SLAM) of the smart mower, and generating a navigation or mowing action instruction.