Robot Balance Control Using Aggregate Orientation Estimation
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Solution Overview
Problem
Existing robotic systems face challenges in accurately estimating and maintaining balance due to inaccuracies in orientation and angular velocity measurements, particularly when limbs are oriented and moving in ways that contradict sensor readings, leading to potential instability.
Innovation Solution
A robotic device is equipped with sensors to measure joint angles and base orientation, a processing system to estimate aggregate orientation and angular velocity based on kinematic relationships, and a control system to adjust limb movements for balance, using a feedback-based state observer to reduce noise in angular momentum estimates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensor measurements of base orientation are used directly for balance control, then the control system is simple, but the balance accuracy deteriorates due to inaccuracies when limbs are oriented and moving in ways that contradict sensor readings
Solution Approach 1:
The patent introduces an intermediary processing system that acts as a mediator between the sensors and the control system. This processing system estimates the aggregate orientation and angular velocity of the robotic device by combining base orientation sensor readings with limb angle measurements and kinematic relationships, thereby improving measurement accuracy without directly increasing control system complexity
Solution Approach 2:
The patent replaces direct reliance on mechanical sensor readings with a computational estimation approach. Instead of using raw sensor measurements directly for control, the system uses processing power to calculate estimated orientation and angular velocity based on kinematic models and multiple sensor inputs, substituting mechanical measurement limitations with computational solutions
2Reliability
If the control system uses aggregate orientation and angular velocity estimates, then balance control accuracy is improved, but the computational complexity and processing requirements increase
Solution Approach 1:
The patent implements feedback mechanisms where the processing system continuously estimates aggregate orientation and angular velocity, compares these estimates with desired states, and adjusts control signals accordingly. This feedback loop improves balance control reliability by dynamically compensating for measurement inaccuracies and maintaining accurate state estimation
Solution Approach 2:
The processing system performs multiple functions simultaneously: it processes sensor data, estimates aggregate orientation, calculates angular velocity, and provides control signals. This multi-functionality approach consolidates computational tasks into a single integrated system, managing computational complexity through functional consolidation rather than requiring separate dedicated systems for each task
Data Source
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AI summary
A control system may receive a first plurality of measurements indicative of respective joint angles corresponding to a plurality of sensors connected to a robot. The robot may include a body and a plurality of jointed limbs connected to the body associated with respective properties. The control system may also receive a body orientation measurement indicative of an orientation of the body of the robot. The control system may further determine a relationship between the first plurality of measurements and the body orientation measurement based on the properties associated with the jointed limbs of the robot. Additionally, the control system may estimate an aggregate orientation of the robot based on the first plurality of measurements, the body orientation measurement, and the determined relationship. Further, the control system may provide instructions to control at least one jointed limb of the robot based on the estimated aggregate orientation of the robot.