Human-Robot Interactive System Stiffness Estimation Control
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Solution Overview
Problem
Human-robot interactive systems face challenges in accurately defining a human model and achieving natural interaction due to varying operator stiffness, which affects control stability and performance.
Innovation Solution
A system with a controller and operator-robot interface that measures operator input force and muscle activation levels to calculate stiffness, automatically adjusting control sensitivity of the robot's powered elements for optimized stability and performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the robot uses fixed control sensitivity, then the control system is simple, but control stability deteriorates when operator stiffness varies
Solution Approach 1:
The control sensitivity is made dynamic rather than fixed. The system continuously estimates operator stiffness and adjusts control sensitivity in real-time based on the estimated stiffness values, allowing the control parameters to adapt to varying operator conditions and maintain stability
Solution Approach 2:
The system implements feedback by measuring operator input force, estimating stiffness from force and position data, and using this information to adjust control sensitivity. This closed-loop approach ensures control stability adapts to changing operator states
2Reliability
If the robot adjusts control sensitivity dynamically, then control stability improves, but device complexity increases
Solution Approach 1:
The patent replaces complex mechanical adjustment mechanisms with computational estimation and software-based control sensitivity adjustment. The stiffness estimation algorithm and adaptive control sensitivity adjustment are implemented through software processing of sensor data, avoiding additional mechanical complexity
3Measurement precision
If the system uses simple force sensing, then device complexity is low, but measurement precision of operator stiffness is insufficient
Solution Approach 1:
The system uses an intermediary estimation algorithm that processes readily available force and position sensor data to derive stiffness information. Rather than requiring direct stiffness sensors, the algorithm acts as an intermediary that extracts stiffness characteristics from existing measurements, achieving precise stiffness assessment without complex sensing hardware
Data Source
AI summary
A robotic system includes a robot adapted for moving a payload in proportional response to an input force from an operator, sensors adapted for measuring a predetermined set of operator input values, including the input force, and a controller. The controller determines a changing stiffness value of the operator using set of operator input values, and automatically adjusts a level of control sensitivity over the robot using the stiffness value. The input values include the input force, a muscle activation level of the operator, and a position of the operator. A method of controlling the robot includes measuring the operator input values using the plurality of sensors, processing the input values using the controller to thereby calculate the stiffness value, and automatically adjusting the level of control sensitivity over the robot using the stiffness value. A specific operator may be identified, with control sensitivity being adjusted based on the identity.