Robot Trajectory Control via Viscosity Volume Model
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Solution Overview
Problem
Existing methods for controlling robot movements in three-dimensional space struggle to find the shortest collision-free trajectory while adhering to speed limitations and avoiding singularities, especially in flexible and dynamic environments like Industry 4.0 scenarios, where manual checking becomes increasingly difficult.
Innovation Solution
A method involving the creation of a viscosity volume model with spatial regions of varying viscosities, where the robot's movement is simulated as a liquid flowing through these regions, allowing for the detection of a collision-free path that avoids singularities by assigning high viscosities to sensitive areas, ensuring the robot moves within specified speed limits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If a shortest path trajectory is calculated in three-dimensional space, then path efficiency is improved, but collision risk increases and singularity avoidance becomes difficult
Solution Approach 1:
The patent introduces a viscosity volume model as an intermediary representation of the working environment. This model uses spatially varying viscosity values to encode obstacle information and robot constraints, serving as a mediator between the desired trajectory and the physical environment. The liquid flow simulation through this viscosity field automatically generates collision-free paths without requiring complex collision detection algorithms.
Solution Approach 2:
The patent replaces traditional mechanical trajectory planning methods with a fluid dynamics-based approach. Instead of using geometric algorithms and collision detection mechanics, the system uses liquid flow simulation through a viscosity volume model to naturally generate safe trajectories. The fluid's physical behavior inherently avoids high-viscosity regions (obstacles) and follows optimal flow paths.
2Reliability
If manual trajectory checking is performed to ensure feasibility, then robot safety is improved, but operational complexity increases and automation decreases
Solution Approach 1:
The viscosity volume model with liquid flow simulation performs self-service trajectory validation. The fluid dynamics automatically ensure that generated trajectories respect robot constraints and avoid obstacles without requiring external manual checking. The system self-regulates trajectory feasibility through the physical laws governing fluid flow through viscous media.
Solution Approach 2:
The patent transforms the trajectory planning problem from a geometric constraint satisfaction problem into a fluid flow problem with variable viscosity parameters. By changing the representation from discrete obstacle coordinates to continuous viscosity fields, the system enables automatic feasibility assessment through fluid simulation, eliminating the need for manual trajectory verification.
3Reliability
If speed limits are enforced to avoid singularities, then robot reliability is improved, but productivity decreases
Solution Approach 1:
The patent introduces dynamic speed adjustment through the liquid flow simulation. The velocity of the liquid at different spatial locations naturally adapts to local viscosity conditions, allowing faster movement in safe regions and automatic slowing near obstacles or singularities. This dynamic speed profiling maintains reliability while maximizing overall productivity compared to uniform speed limits.
Solution Approach 2:
The system uses periodic sampling of the viscosity volume model along the trajectory to determine appropriate speed adjustments. By periodically evaluating the local viscosity conditions and adjusting speed accordingly, the robot can maintain high speeds over most of the path while automatically reducing speed only when necessary to avoid singularities or obstacles.
Data Source
Figure 1
Figure 2A~2B
Figure 2C~2D
AI summary
The invention relates to a method for controlling a robot movement of a robot based on a second trajectory, wherein the second trajectory is calculated based on a viscosity volume model.