Wall-Climbing Robot Path Planning for Stable Lane Changes
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing path planning methods for wall-climbing robots, particularly those used in ship derusting, face challenges such as inefficient straight crawling, inconsistency in derusting quality due to N-shaped or Z-shaped trajectories, and the tail falling phenomenon during horizontal operations, which reduces efficiency and requires manual adjustments.
Innovation Solution
A path planning method that includes establishing a spatial pose model, performing statics and kinetics analysis to determine crawling and steering capabilities, and implementing automated path planning for vertical and horizontal modes, including automatic lane changing and compensation for the tail falling phenomenon.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If straight crawling trajectory is used, then the robot structure is simple, but the derusting efficiency is low and the robot cannot crawl back and forth
Solution Approach 1:
The patent implements dynamic path planning that allows the robot to automatically switch between straight crawling, N-shaped trajectory, and zigzag trajectory based on real-time operational needs. This dynamic adaptation enables the robot to maintain simple structure while achieving high derusting efficiency through automated trajectory selection and execution.
2Adaptability or versatility
If N-shaped (Z-shaped) trajectory is used, then the robot can change direction, but the derusting quality consistency is poor and steering performance requirements are high
Solution Approach 1:
The patent incorporates feedback mechanisms where the robot's position, orientation, and operational status are continuously monitored. Based on this feedback, the path planning system automatically adjusts the trajectory to maintain consistent derusting quality across different sections, eliminating the quality inconsistency problems associated with manual N-shaped trajectories.
Solution Approach 2:
The robot performs self-navigation and self-adjustment through automated path planning, eliminating the need for high-precision manual steering operations. The system automatically calculates and executes the optimal trajectory, reducing both the skill requirement for operators and the variability in derusting quality.
3Ease of operation
If manual lane changing operation is used, then the operator can adjust the path, but the operation efficiency is reduced and experience dependency increases
Solution Approach 1:
The patent implements automated lane changing and path adjustment functions where the robot independently plans and executes its own trajectory modifications based on pre-set parameters and real-time conditions. This eliminates manual intervention entirely, improving operational efficiency while removing experience dependency through algorithmic decision-making.
4Area of stationary object
If the robot travels horizontally, then the coverage area increases, but the tail falling phenomenon occurs and manual adjustment is required
Solution Approach 1:
The patent applies preliminary counterbalancing actions by calculating the gravitational effects on the robot's components (including the high-pressure water pipe and recycling pipe) before horizontal movement. The path planning system pre-compensates for the tail falling phenomenon by adjusting the trajectory in advance, allowing the robot to maintain stable horizontal travel over extended distances without manual intervention.
5Length of stationary object
If the climbing height increases, then the vertical coverage improves, but the center of gravity shifts and angle deviation increases
Solution Approach 1:
The patent calculates the shifting center of gravity and resulting angle deviation in advance based on the robot's mass distribution and climbing height. The path planning system pre-compensates for these changes by adjusting the trajectory parameters before execution, maintaining high position accuracy even at significant climbing heights without requiring manual adjustment.
Data Source
Figure 1~2(c)
Figure 3~4
Figure 5~6
AI summary
The present disclosure provides a path planning method for a wall-climbing robot. The method includes the following steps: step 1, establishing a spatial pose model of a wall-climbing robot during a working process; step 2, performing statics analysis on the wall-climbing robot, and decomposing a resultant force G of the gravity of the wall-climbing robot itself and the gravity of a load borne by the wall-climbing robot; step 3, performing kinetics analysis on the wall-climbing robot, and analyzing the crawling capability and steering capability thereof; and step 4, performing path planning according to analysis results of the crawling capability and the steering capability. The method is used for solving the problems of a traditional robot being controlled by an operator using a wireless remote to control the movement, lane changing and straight walking of the robot, and the operator being required to continuously operate the robot during the whole process of operating same, which greatly consumes the time and energy of personnel and increases labor costs. By means of the present application, automated operation for path planning, straight walking and lane changing of a wall-climbing robot is implemented, so that an operator is freed from frequently operating a remote and performing real-time monitoring, and the robot is more intelligent.