Sensor Fusion for Balancing Robots Using Indirect Actuator Data
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Solution Overview
Problem
Balancing robots face challenges in maintaining stability due to their statically unstable nature, requiring active balancing mechanisms that can be complex and costly, especially when disturbances occur, and often necessitate multiple sensors to measure properties directly.
Innovation Solution
The use of indirect sensor data from a variety of sensors, such as position and velocity data from actuators, to determine properties like pitch angle, potentially omitting the need for direct sensors like inclinometers, and combining multiple measures using statistical methods to ensure accuracy and robustness in control commands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If direct sensors (e.g., inclinometers) are used to measure properties like pitch angle, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent uses actuator position and velocity sensors as intermediary elements to indirectly determine pitch angle. Instead of directly measuring pitch angle with an inclinometer, the system measures actuator states (which are easier to obtain) and uses these as intermediaries to compute the desired property through dynamic models, thereby avoiding additional direct sensors
Solution Approach 2:
The patent replaces mechanical direct measurement systems (inclinometers) with a computational approach using dynamic models. The mechanical sensing of pitch angle is substituted by mathematical computation from actuator sensor data, eliminating the need for separate mechanical sensing devices
2Reliability
If multiple sensors are used to directly measure properties, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent makes existing actuator sensors serve multiple functions: they not only control the actuators but also provide data for determining pitch angle and other robot properties. This multi-functionality increases reliability without adding dedicated sensors for each measurement
Solution Approach 2:
The patent merges the measurement function into the existing actuator control system. The same sensors that monitor actuator position and velocity are combined with dynamic models to simultaneously determine robot configuration and orientation, consolidating multiple measurement functions into a unified system
3Device complexity
If indirect sensor data is used to determine properties, then device complexity is reduced, but measurement precision may worsen
Solution Approach 1:
The patent employs feedback through dynamic models that continuously process actuator position and velocity data to determine robot properties. The model-based approach provides continuous feedback about system state, maintaining precision through computational processing rather than direct sensing
Solution Approach 2:
The patent transforms the measurement approach by changing parameters from direct physical measurement to computational derivation. By using actuator state parameters (position, velocity) and transforming them through dynamic models, the system maintains measurement precision through mathematical relationships rather than direct sensing
Data Source
AI summary
Methods, apparatus, and computer readable media applicable to robots, such as balancing robots. Some implementations are directed to determining multiple measures of a property of a robot for a given time and determining a final measure of the property of the robot for the given time based on the multiple measures. One or more control commands may be generated based on the final measure of the property and provided to one or more actuators of the robot.