Industrial Robot Motion Path Energy Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for programming industrial robots focus on creating collision-free motion paths that minimize time consumption, but do not effectively consider energy efficiency, leading to suboptimal energy usage during task performance.
Innovation Solution
A method and data processing system that identify and select energetically optimized motion paths for industrial robots by analyzing key points, applying physics and kinematics to reduce energy consumption while meeting timing and geometric constraints, and storing energy consumption data for improved path optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If motion paths are optimized to minimize time consumption, then productivity is improved, but energy consumption increases
Solution Approach 1:
The system changes motion parameters (velocity, acceleration, jerk) dynamically along the motion path based on energy efficiency calculations. By adjusting these parameters according to the robot's dynamic model and task requirements, the system achieves energy-optimized motion profiles that balance speed and energy consumption.
Solution Approach 2:
The motion paths are made dynamic and adaptive rather than static. The system continuously evaluates energy consumption during path execution and adjusts motion parameters in real-time based on the robot's current state, task requirements, and energy efficiency criteria, enabling flexible optimization.
2Use of energy by moving object
If energy optimization is implemented in motion path programming, then energy consumption is reduced, but computational complexity increases
Solution Approach 1:
The system replaces traditional mechanical motion programming with a computational energy optimization model. By using a physics-based dynamic model and energy consumption calculations, the system automatically generates optimized motion paths without requiring complex manual programming, substituting computational intelligence for mechanical expertise.
Solution Approach 2:
The motion programming system performs self-optimization by automatically calculating energy consumption and adjusting motion parameters without external intervention. The system uses its own dynamic model and energy criteria to generate optimized paths autonomously, reducing the need for complex external control mechanisms.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Various disclosed embodiments include methods, systems, and computer-readable media for identifying a motion path for an industrial robot. According to one embodiment, a method includes identifying a plurality of points at which at least one component of the industrial robot is positioned during performance of a task. The identified points include at least a starting point and an ending point of the component for performing the task. The method also includes generating one or more motion paths for the industrial robot to perform the task based on the identified points. The method further includes identifying and predicting energy consumption by the industrial robot for the one or more generated motion paths. The method also includes selecting the motion path for the industrial robot based on the identified energy consumption. Additionally, the method includes storing information about the energy consumption by the industrial robot for the selected motion path.