Marine Debris Robot Path Planning Under Dynamic Water Currents
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Solution Overview
Problem
Existing path planning methods for marine debris collection by robots assume a static marine environment, leading to inefficiencies and increased energy consumption due to unnecessary path repetition and failure to collect dynamic marine debris.
Innovation Solution
An efficient path planning method using depth-first search (DFS) to sequence target positions and a modified A-star (MA*) algorithm to determine the next target position with the lowest total cost, considering actual, estimated, and adaptive costs, including the impact of water currents on travel time and energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the robot traverses the entire area based on full coverage (SMURF algorithm), then all areas are covered, but time and electricity costs are wasted
Solution Approach 1:
The patent extracts only the necessary target positions (marine debris locations) from the entire search area, rather than traversing all positions. The A* algorithm plans paths to these extracted target positions, eliminating unnecessary path traversal while ensuring all debris are collected.
Solution Approach 2:
The patent performs preliminary detection to identify marine debris positions before path planning. The DFS algorithm pre-processes the search area to locate all target positions, and the A* algorithm uses these pre-identified positions to plan efficient paths, avoiding random or exhaustive traversal.
2Device complexity
If the robot assumes a static marine environment, then path planning is simplified, but dynamic marine debris cannot be collected
Solution Approach 1:
The patent implements feedback mechanisms where the robot continuously detects marine debris positions during movement. The A* algorithm replans paths based on real-time debris locations and water current conditions, allowing the system to adapt to dynamic environmental changes while maintaining manageable complexity through iterative refinement.
3Device complexity
If the robot does not consider water current direction, then path planning is simpler, but energy consumption increases
Solution Approach 1:
The patent incorporates water current parameters (direction and speed) into the path planning process. The A* algorithm evaluates multiple path options considering current assistance, selecting routes that leverage favorable currents to reduce energy consumption while avoiding paths that would require excessive energy to overcome strong opposing currents.
Data Source
AI summary
An efficient path planning method for a robot used for collecting marine debris includes: traversing all target positions of the marine debris by depth-first search (DFS) to generate a target position sequence; and calculating a target position with a lowest total cost by a path planning algorithm, and setting the target position with the lowest total cost as a next target position to be traversed for the robot. The efficient path planning method can plan an optimal or near-optimal cleaning path for the robot based on real-time environmental information, reducing unnecessary path repetition and ineffective motion, thereby significantly improving the cleaning efficiency.