Hierarchical Passivity Control for Stable Robot-Human Interaction
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Solution Overview
Problem
Existing robotic interaction systems face instability and discomfort due to factors like control system limitations, human variability, and communication delays, leading to negative consequences in human-robot-human interactions.
Innovation Solution
A passivity framework is introduced that separates input and output energy at each port, using hierarchical optimization to modulate energy flow and ensure that output energy is less than input energy, ensuring stability and comfort by prioritizing tasks with different constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional control systems are used in human-robot interaction, then the system can operate with basic functionality, but the system becomes unstable and uncomfortable due to control limitations, human variability, and communication delays
Solution Approach 1:
The control system is segmented into multiple hierarchical levels with different priority constraints. The passivity framework divides the control problem into energy management at each port and task-specific constraints, allowing independent optimization of stability and performance without requiring a completely complex monolithic controller
Solution Approach 2:
The system dynamically changes control parameters based on energy flow conditions and task priorities. By adjusting impedance parameters and energy dissipation rates according to the passivity framework, the system maintains stability across varying interaction conditions without requiring overly complex adaptive control mechanisms
2Reliability
If the robot enforces strict constraints to ensure stability, then system reliability improves, but the interaction becomes less adaptable to human variability and task requirements
Solution Approach 1:
The control system dynamically adjusts constraints based on task priority and interaction conditions. High-priority safety and passivity constraints are enforced strictly, while lower-priority task-specific constraints are adjusted adaptively, allowing the system to maintain stability while being versatile across different interaction scenarios
Solution Approach 2:
Different levels of constraint enforcement are applied to different aspects of the interaction. The passivity framework applies strict energy dissipation constraints at the system level for stability, while allowing more flexible task-specific constraints at the application level, enabling both reliability and adaptability
3Reliability
If the system uses simple energy management to maintain passivity, then computational requirements are reduced, but the system cannot handle multiple concurrent tasks with different priorities
Solution Approach 1:
The constraint management is segmented into hierarchical levels where the passivity framework handles energy management at one level and task-specific constraints are handled at another level. This segmentation allows the system to maintain passivity with relatively simple energy monitoring while managing multiple prioritized tasks through hierarchical optimization
Solution Approach 2:
The system uses feedback from energy flow measurements to adjust constraint enforcement in real-time. By monitoring energy dissipation at each port and providing feedback to the hierarchical constraint solver, the system maintains passivity while adapting to varying task requirements without requiring overly complex open-loop control
Data Source
AI summary
Systems and methods for passive robot-mediated physical human-human interaction using hierarchical constraints. The system enforces constraints on both sides of a bilateral physical interaction with different priorities on each side in the presence of time-varying destabilizing factors such as control system limitations, human variability, hard contacts, relaxed user grasps, stiff control settings, and/or communication delays. A hierarchical optimization framework is provided to satisfy these constraints. A back-up passivity control may also be included to ensure optimization at both sides.