Robot Cell Layout Planning With Staged Pose and Route Search
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Solution Overview
Problem
Current robot cell system design methods require extensive manual effort and time due to the need for trial and error in determining the layout and operation of robots, and existing metaheuristic calculation methods are inefficient, leading to long calculation times and impractical optimization of robot operations.
Innovation Solution
A robot cell system design device that includes an acquisition unit for gathering specifications, a layout planning unit for calculating layout candidates, a pose planning unit for determining optimal start and end poses, a route planning unit for calculating routes, and an evaluation unit for selecting the most efficient layout based on cost and constraints, reducing the time required for system design.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If metaheuristic calculation is used to update layout by evaluating enormous layout patterns and operation patterns in a brute-force manner, then the layout optimization is performed, but the calculation time becomes long
Solution Approach 1:
The patent divides the layout optimization process into multiple stages: initial layout generation, metaheuristic optimization, and local search refinement. By segmenting the optimization process, the system can efficiently explore the solution space without requiring exhaustive brute-force evaluation of all possible layouts, thus reducing calculation time while maintaining optimization quality.
Solution Approach 2:
The patent performs preliminary actions by generating an initial layout and performing preliminary metaheuristic optimization before conducting the final local search. This preliminary action reduces the search space for the subsequent local search phase, allowing the system to achieve better optimization results faster without evaluating all possible layouts.
2Productivity
If a person determines the layout of the robot and each member and the operation of the robot by trial and error until the operation time of the system reaches a target, then the system operation time is optimized, but it takes a lot of man-hours and time
Solution Approach 1:
The patent implements self-service by enabling the system to automatically perform layout optimization and operation time reduction through integrated metaheuristic calculation and local search algorithms. The system autonomously evaluates multiple layout patterns and operation patterns, identifies optimal configurations, and generates improved layouts without requiring manual trial and error, thereby significantly reducing design time while achieving operation time optimization.
3Manufacturing precision
If enormous layout patterns and operation patterns are evaluated in a brute-force manner, then comprehensive optimization is achieved, but the calculation time becomes long
Solution Approach 1:
The patent applies dynamics by implementing a two-phase optimization approach where the search strategy dynamically adapts based on the optimization stage. In the initial phase, metaheuristic algorithms perform broad exploration of the solution space. In the final phase, local search algorithms perform intensive exploitation around promising solutions. This dynamic adaptation allows comprehensive optimization without requiring brute-force evaluation of all possible layouts, significantly reducing calculation time.
Solution Approach 2:
The patent changes parameters by transitioning from global metaheuristic optimization parameters to local search parameters. The system adjusts the evaluation criteria and search depth based on the optimization phase, allowing comprehensive layout optimization in the metaheuristic phase and precise local refinement in the local search phase, achieving high optimization precision without exhaustive brute-force calculation.
Data Source
AI summary
An acquisition unit acquires specification information about a robot that is a component of a robot cell system, member information including shape information about a member, other than the robot, which is also a component of the robot cell system, and work information relating to work to be performed by the robot. A layout planning unit calculates, based on the specification information, the member information, and the work information, one or more layout candidates for the robot and the member in the robot cell system. A pose planning unit calculates, for each layout candidate, a set of combinations of a start pose at a start point and an end pose at an end point of each operation of the robot. A route planning unit calculates, for each layout candidate, a set of routes from the start pose to the end pose of each combination of the start pose and the end pose.