Wheel-Legged Robot Control Using Nonlinear and Whole-Body Dynamics
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Solution Overview
Problem
Wheel-legged robots face challenges in achieving stable and flexible control for complex actions such as jumping, somersaults, and step walking, due to their unstable underactuated nature.
Innovation Solution
A method involving the use of current motion state data to input into a nonlinear controller, which generates a target joint angular acceleration reference value. This value is then input into a whole-body dynamics controller to output joint torque for controlling the robot's actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a whole-body dynamics controller is used to control task performing processes, then the robot can complete simple actions, but the control stability deteriorates when the distance from the balance point exceeds the controllable range of linearization
Solution Approach 1:
The controller is divided into two independent modules: a nonlinear controller responsible for balance control and a whole-body dynamics controller responsible for task execution. The nonlinear controller specifically handles balance stabilization when the robot is far from the balance point, while the whole-body dynamics controller executes complex tasks. This segmentation allows each module to specialize in its function, resolving the contradiction between handling complex actions and maintaining balance stability.
Solution Approach 2:
The nonlinear controller acts as an intermediary between the whole-body dynamics controller and the robot's balance system. It receives state information from the whole-body dynamics controller and generates corrective torque commands to maintain balance, especially when the robot is far from the balance point. This intermediary structure enables the system to handle complex actions while maintaining balance stability through coordinated control.
2Device complexity
If linearization control is used, then the balance control is simple to implement, but it becomes ineffective when the distance from the balance point exceeds the controllable range
Solution Approach 1:
The system switches between linearization control and nonlinear control based on the robot's state. When the distance from the balance point is within the controllable range, linearization control is used for simplicity. When the distance exceeds the controllable range, nonlinear control takes over to expand the controllable range. This dynamic parameter change approach resolves the contradiction between control simplicity and controllable range.
Data Source
AI summary
A method includes: obtaining current motion state data of the wheel-legged robot, the current motion state data representing motion features of the wheel-legged robot, inputting the current motion state data into a nonlinear controller to obtain a target joint angular acceleration reference value of a target robot joint of the wheel-legged robot, and inputting the target joint angular acceleration reference value into a whole-body dynamics controller to output a joint torque for controlling the wheel-legged robot to perform a control task.