Robotic Motion Retargeting for Vibration Suppression and Dynamic Balancing
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Solution Overview
Problem
Robotic systems experience unwanted vibrations during rapid movements, making it challenging to replicate human-like motions and animations, as they are designed to be stiff but often fail to behave like idealized mechanical systems due to compliance and deformation in joints and components.
Innovation Solution
A computational method for generating control signals that uses dynamic simulation to predict and minimize vibrations by optimizing motor trajectories, allowing for the use of lighter and less expensive robotic systems, and incorporating dynamic balancing to reduce motor torques and suppress vibrations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If robotic systems are designed to be stiff to reduce vibrations, then vibration suppression is improved, but the system weight increases and requires stronger motors
Solution Approach 1:
The patent replaces mechanical stiffness (physical property) with computational vibration suppression (control algorithm). The system uses dynamic simulation and optimization to generate control signals that counteract vibrations, eliminating the need for heavy stiffening structures. This substitutes a mechanical solution with a computational one, allowing lightweight designs while maintaining vibration suppression.
Solution Approach 2:
The patent changes the control parameters dynamically by optimizing motor trajectories based on simulated vibrations. The control system adjusts motion parameters in real-time to minimize vibrations, replacing the static approach of mechanical stiffening with dynamic parameter optimization. This allows the system to maintain performance with lighter components.
2Object-affected harmful factors
If robotic systems are designed to be stiff to reduce vibrations, then vibration suppression is improved, but motor torque requirements increase
Solution Approach 1:
The patent replaces mechanical torque (physical force) with computational optimization (control algorithm). By using dynamic simulation to predict and optimize motor trajectories, the system generates control signals that minimize vibrations without requiring excessive motor torque. This substitutes a mechanical force-based solution with a computational optimization approach.
Solution Approach 2:
The patent performs preliminary optimization of motor trajectories through dynamic simulation before executing the motion. By pre-calculating the optimal control signals that minimize vibrations, the system avoids the need for high torque during vibration suppression. This preliminary computational action prevents the need for mechanically oversized motors.
3Object-affected harmful factors
If animations are slowed down to avoid vibrations, then vibration suppression is improved, but the productivity and expressiveiveness of robotic movements deteriorate
Solution Approach 1:
The patent replaces mechanical slowing (reducing speed) with computational optimization (trajectory optimization). Instead of slowing down movements to avoid vibrations, the system uses dynamic simulation to optimize motor trajectories that maintain high speeds while minimizing vibrations. This substitutes a speed-reduction approach with a computational optimization approach.
Solution Approach 2:
The patent introduces dynamics to the control approach by optimizing motor trajectories based on dynamic simulation of vibrations. Rather than using static speed reduction, the system dynamically adjusts control signals to minimize vibrations at each point in the motion, enabling fast movements without excessive vibrations. This dynamic control approach maintains productivity while suppressing vibrations.
4Object-affected harmful factors
If manual tuning of motion trajectories is performed to avoid vibrations, then vibration suppression is improved, but the complexity and time required for animation production increases
Solution Approach 1:
The patent replaces manual tuning (human operation) with automated computational optimization (algorithm). The dynamic simulation and trajectory optimization process automatically generates vibration-minimizing control signals without requiring manual intervention. This substitutes a manual, experience-based approach with an automated computational system, reducing complexity in the long run.
Solution Approach 2:
The patent enables the system to self-optimize its motion trajectories through automated dynamic simulation and optimization. The computational system independently generates optimal control signals without requiring external manual tuning, making the process self-sufficient. This automation eliminates the need for continuous manual intervention while maintaining vibration suppression.
Data Source
AI summary
A system providing dynamic balancing in a robotic system. The system includes memory storing a definition of a robot and storing an input animation for the robot specifying motion of components of the robot. A simulator performs a dynamic simulation of the robot performing the input animation including modeling a first set of the components as flexible components and a second set of the components as rigid components. Each of the flexible components is coupled at opposite ends to one of the rigid components. An optimizer generates a retargeted motion for the components to provide dynamic balancing of the robot performing the retargeted motion. The optimizer generates the retargeted motion by transforming forces acting on the robot to a local contact frame rigidly moving with the robot. The optimizer generates the retargeted motion so a zero-moment point of the robot lies in a support area of the robot's feet.