Robot Safety Control Using CBF-Based Safe Velocity Tracking
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Solution Overview
Problem
Current control systems for robotics platforms require full knowledge of high-fidelity dynamical models to ensure safety, which is not always possible, and even with control barrier functions (CBFs), safety cannot be guaranteed due to model uncertainty.
Innovation Solution
A model-free safety controller that uses control barrier functions (CBFs) to define safe regions in the configuration space, computes safe velocities based on reduced-order kinematics, and instructs actuators to track these velocities, ensuring safety without relying on full dynamical models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If full knowledge of high-fidelity dynamical models is used to ensure safety, then safety guarantees can be obtained, but model uncertainty prevents safety guarantees even with control barrier functions
Solution Approach 1:
The patent extracts the essential safety-critical elements from complex dynamical models by using reduced-order models that capture only the necessary dynamics for safety analysis. This allows control barrier functions to be applied without requiring complete knowledge of the full system dynamics, thereby achieving safety guarantees while reducing model complexity requirements.
Solution Approach 2:
The patent changes the parameters of the dynamical model by transitioning from high-fidelity complex models to reduced-order models with fewer parameters. This parameter reduction maintains the essential safety-critical dynamics while eliminating unnecessary complexity, enabling practical implementation of model-free safety control.
2Reliability
If control barrier functions are used to compute safe velocities, then safety can be maintained, but tracking safe velocities requires high computational speed
Solution Approach 1:
The patent performs preliminary computation of control barrier function parameters offline or in advance, preparing safety certificates and reduced-order model parameters before real-time operation. This preliminary action reduces the computational burden during real-time control, allowing safe velocity computation to be performed at the required high speed without compromising safety guarantees.
Data Source
AI summary
Systems and methods for model-free safety control of robotic platforms in accordance with embodiments of the invention are illustrated. One embodiment includes a robot, including a set of one or more actuators, and at least one sensor. The robot further includes a controller including a set of one or more processors and a memory including a controller application, where the controller application configures the set of processors to control the robot by performing the steps of defining a safe set identifying positions where the robot is safe, determining a control barrier function (CBF) based on the safe set, computing a safe velocity based on the CBF and a current position of the robot such that the robot remains in the safe set, and instructing the robot to track to the safe velocity.