Robot Trajectory Control Using Offline Path Prediction
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Solution Overview
Problem
Existing methods for programming robot movement trajectories are computationally heavy, time-consuming, and require extensive manual testing to achieve time-optimal paths, which is challenging for users lacking sufficient knowledge, and there is a lack of user-friendly tools for finding optimal trajectories.
Innovation Solution
A method and control system that predict values of parameters related to alternative movement trajectories offline, allowing for the selection and execution of optimal or near-optimal trajectories using a programming tool that automatically suggests the best path based on user input, considering parameters like time, energy, and robot constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If spline search is used to find time-optimal movement trajectory, then the optimal trajectory can be found, but the computational load becomes very heavy
Solution Approach 1:
The patent segments the continuous trajectory optimization problem into discrete alternative trajectories that can be pre-calculated and stored. Instead of performing continuous spline search computations, the system divides the solution space into manageable segments (pre-defined trajectories) that can be evaluated and selected based on predicted performance parameters.
Solution Approach 2:
The patent applies preliminary action by pre-calculating and storing multiple alternative movement trajectories along with their predicted parameter values before actual robot execution. This offline preparation eliminates the need for heavy computational searches during runtime, as the optimal trajectory can be directly selected from pre-evaluated options.
2Measurement precision
If manual testing is carried out to program time-optimal movement trajectory, then the optimal trajectory can be achieved, but the process becomes time-consuming and requires extensive user knowledge
Solution Approach 1:
The system performs self-service by automatically predicting parameter values for alternative trajectories and selecting the optimal one without requiring manual user intervention or testing. The control system autonomously evaluates trajectories based on predicted parameters and executes the selected trajectory, eliminating the need for users to perform time-consuming manual tests.
Solution Approach 2:
The patent replaces manual mechanical testing and adjustment processes with automated computational prediction and selection. Instead of physically testing different trajectories through manual programming and observation, the system uses algorithmic prediction of parameter values to identify the optimal trajectory, substituting physical trial-and-error with virtual evaluation.
3Productivity
If extensive manual testing is performed to find optimal trajectory, then time-optimal path can be achieved, but the operation becomes complex and difficult for users without sufficient knowledge
Solution Approach 1:
The system autonomously handles the complex task of trajectory optimization by automatically predicting parameters and selecting the optimal trajectory from alternative options. Users simply need to provide basic input parameters, and the system performs the sophisticated optimization independently, making the process accessible to users regardless of their expertise level.
Solution Approach 2:
The patent introduces an intermediary layer (the control system with prediction algorithms) that mediates between simple user inputs and complex trajectory optimization requirements. This intermediary automatically processes user requirements, evaluates alternative trajectories, and translates them into optimized motion commands, shielding users from the underlying complexity.
Data Source
AI summary
A method for controlling movement trajectories of a robot, the method including predicting, in an offline mode, values of at least one parameter related to the execution of alternative movement trajectories between a first position of the robot and a second position of the robot; selecting, in the offline mode, a movement trajectory based on the predicted values of the at least one parameter; and executing the selected movement trajectory by the robot. A control system for controlling movement trajectories of a robot is also provided.