Robot Motion Optimization Using Bell-Shaped Velocity Profiles
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Solution Overview
Problem
Humanoid robots face challenges in performing rapid and dynamic motions similar to human actions, such as throwing or kicking, due to the complexity of controlling multiple joints and achieving optimal physical ranges, which requires advanced motion optimization techniques.
Innovation Solution
A method involving the formation of bell-shaped velocity profiles for robot joints and center of gravity trajectories, with an objective function that maximizes end effector velocity, limits joint velocity and torque, and maintains the Zero Momentum Point within a specific range, allowing for optimized motion control and dynamic performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the robot uses feedback control with sensors for motion control, then the robot can maintain stability and accuracy, but the motion speed is slow and the system complexity increases
Solution Approach 1:
The patent pre-optimizes motion trajectories using bell-shaped velocity profiles and objective functions before execution. The controller pre-calculates optimal joint velocities and accelerations that maximize dynamic performance while satisfying constraints, eliminating the need for slow feedback adjustments during motion execution. This transforms real-time feedback control into pre-planned open-loop control with superior speed and performance.
2Power
If the robot performs rapid and dynamic motions similar to human actions, then the dynamic performance improves, but the control difficulty and joint coordination complexity increase significantly
Solution Approach 1:
The patent transforms the control problem by changing parameters from direct joint position control to bell-shaped velocity profile parameters. By optimizing velocity profiles with specific mathematical forms (bell-shaped curves) and their parameters (amplitude, width, timing), the system achieves complex dynamic motions through simplified parameter adjustment rather than complex multi-joint coordination, reducing control complexity while maintaining high dynamic performance.
Solution Approach 2:
The patent introduces dynamic optimization by formulating and solving objective functions that maximize dynamic performance metrics (such as end-effector velocity or kinetic energy) subject to joint constraints. The bell-shaped velocity profiles are dynamically adjusted based on task requirements, allowing the robot to achieve human-like rapid motions through dynamic parameter optimization rather than static control sequences.
3Productivity
If the robot optimizes motion for maximum velocity and dynamic performance, then the task execution efficiency improves, but the energy consumption and joint torque requirements increase
Solution Approach 1:
The patent incorporates energy and torque constraints as parameters in the bell-shaped velocity profile optimization. By adjusting the shape and timing parameters of the velocity profiles within constrained bounds, the system achieves maximum dynamic performance while preventing excessive energy consumption and joint torque demands. The objective function balances performance maximization with energy efficiency through parameter optimization.
Data Source
AI summary
A robot and a method of controlling the same are disclosed. The robot derives a maximum dynamic performance capability using a specification of an actuator of the robot. The control method includes forming a first bell-shaped velocity profile in response to a start time and an end time of a motion of the robot, calculating a value of an objective function having a limited condition according to the bell-shaped velocity profile, and driving a joint in response to a second bell-shaped velocity profile that minimizes the objective function having the limited condition.