Robot Work Point Distribution via Trajectory Loss Optimization
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Solution Overview
Problem
Existing methods for distributing work points to multiple task-performing robots often lead to excessive concentration on specific robots, increasing the risk of collisions and operational delays due to overlapping work areas.
Innovation Solution
A method involving a computing device that determines available work points for each robot, distributes target work points to minimize differences among robots, predicts target work trajectories, calculates losses based on these trajectories, and re-distributes work points using a genetic algorithm to optimize distribution and reduce collision risks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If work points are distributed to multiple robots, then productivity is improved through parallel task execution, but work points may become excessively concentrated on specific robots leading to increased collision risk
Solution Approach 1:
The patent applies local quality by evaluating and assigning work points based on each robot's specific characteristics, current state, and capabilities. The distribution algorithm considers individual robot attributes (such as position, orientation, and task performance metrics) to assign work points locally optimized for each robot, preventing excessive concentration on any single robot while maintaining overall productivity.
Solution Approach 2:
The patent implements feedback mechanisms by continuously monitoring robot states, task completion progress, and collision risks. The distribution algorithm uses real-time feedback from robot performance and environmental conditions to dynamically adjust work point assignments, ensuring that no single robot becomes overloaded and collision risks are minimized through adaptive redistribution.
2Speed
If work points are concentrated on specific robots, then task execution efficiency is improved, but operational delays occur due to overlapping work areas and collision prevention requirements
Solution Approach 1:
The patent applies dynamics by implementing a dynamic work point distribution system that continuously adapts to changing robot states and environmental conditions. The algorithm dynamically adjusts work point assignments based on real-time robot positions, task progress, and potential collision risks, allowing robots to efficiently execute tasks while automatically redistributing work points to prevent operational delays caused by overlapping work areas.
3Productivity
If multiple robots operate in overlapping work areas, then productivity is enhanced through parallel operations, but collision risk increases requiring operation delays
Solution Approach 1:
The patent applies preliminary action by performing predictive analysis of potential collision risks before robots execute tasks in overlapping work areas. The distribution algorithm evaluates predicted robot trajectories and work area intersections in advance, assigning work points and scheduling operations to prevent collisions before they occur, thereby maintaining productivity without requiring operation delays.
Data Source
AI summary
Disclosed is a method for distributing work points to a plurality of task-performing robots, the method performed by one or more processors of a computing device. The method may include: determining available work points for each of the plurality of task-performing robots; distributing target work points for each of the plurality of task-performing robots based on the determined available work points, and predicting a plurality of target work trajectories for each of the plurality of task-performing robots based on the distributed target work points; calculating a first loss or a second loss based on the predicted plurality of target work trajectories; and re-distributing target work points to each of the plurality of task-performing robots based on at least one of the calculated first loss or the calculated second loss.