Mowing Robot Obstacle Avoidance With Adaptive Path Parameters
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Solution Overview
Problem
Existing mowing robots lack adaptability and flexibility in obstacle avoidance, as they follow a preset path once an obstacle is detected, without adjusting based on the specific obstacle, leading to inefficiencies in various use scenarios.
Innovation Solution
An intelligent obstacle avoidance method that detects obstacles and generates adaptive obstacle avoidance paths with increasing parameters, allowing the mowing robot to bypass obstacles efficiently and flexibly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a preset path is followed for obstacle avoidance, then the obstacle avoidance process is simple to implement, but the adaptability to different obstacles and scenarios is poor
Solution Approach 1:
The patent implements dynamic obstacle avoidance by allowing the robot to adjust its path in real-time based on obstacle detection. Instead of following a fixed preset path, the robot dynamically generates avoidance paths using algorithms like A* or Dijkstra, adapting to different obstacle positions and types during operation.
Solution Approach 2:
The patent changes path planning parameters dynamically based on obstacle characteristics. When obstacles are detected, the system modifies path parameters such as avoidance distance, turning angle, and speed adjustments to adapt to specific obstacle scenarios, thereby improving versatility while maintaining implementation feasibility.
2Device complexity
If a fixed obstacle avoidance method is used, then the system complexity is low, but the obstacle avoidance efficiency is poor
Solution Approach 1:
The patent implements feedback mechanisms where the robot continuously detects obstacles during operation and adjusts its path accordingly. The system uses sensor feedback to identify obstacles, processes this information through path planning algorithms, and dynamically modifies the navigation path to improve avoidance efficiency while managing system complexity through modular architecture.
Solution Approach 2:
The patent performs preliminary path planning before obstacle avoidance is needed, preparing multiple potential paths in advance. When obstacles are detected, the system quickly selects and executes the most appropriate pre-planned path or generates a new one, thereby improving response efficiency without requiring overly complex real-time computation.
3Adaptability or versatility
If adaptive path generation is implemented, then the flexibility and efficiency of obstacle avoidance improve, but the computational complexity increases
Solution Approach 1:
The patent segments the path planning process into distinct modules: obstacle detection, path generation, path evaluation, and execution. Each module handles specific computational tasks independently, allowing the system to achieve high flexibility in adapting to different obstacles while managing computational complexity through divided responsibilities and optimized algorithms.
Data Source
AI summary
Disclosed in the present disclosure is an intelligent obstacle avoidance method. An obstacle in a current path may be detected; a first obstacle avoidance path is generated with a first parameter based on a detection result, and a mowing robot is controlled to operate; if the obstacle is detected again in the first obstacle avoidance path, a second obstacle avoidance path is generated with a second parameter, and the mowing robot is controlled to operate; and the above steps are repeated until the obstacle is bypassed.