Spatial Intent Detection for Interoperable Robot Teleoperation
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Solution Overview
Problem
Current robotic control systems face interoperability issues due to proprietary technologies, leading to high costs and limited compatibility with sensors from different manufacturers, and often rely on high-precision sensing technologies that are not robust or cost-effective for dynamic environmental conditions.
Innovation Solution
A platform-agnostic robotic control system that integrates with various sensors, allowing intuitive control of robotic arms and vehicles using inertial sensors, enabling operation in dynamic environments and supporting interoperability across different robotic platforms, with features like spatial controller input and regime arbitration for precise movement control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If proprietary technology is used in robotic control systems, then control precision is improved, but interoperability deteriorates and cost increases
Solution Approach 1:
The robotic control system is designed with universal compatibility to work with multiple sensor types and manufacturers. The system uses standardized communication protocols and adaptive algorithms that can process data from diverse sensor sources, enabling one control system to serve multiple functions across different robotic platforms without requiring proprietary technology from each manufacturer.
2Measurement precision
If high-precision sensing technology is used, then measurement accuracy is improved, but cost and device complexity increase
Solution Approach 1:
The system dynamically adjusts processing parameters and algorithmic complexity based on the quality and type of sensor data received. Instead of always using high-precision processing, the system adapts its computational approach to match the actual sensor capabilities, achieving accurate control with variable computational complexity rather than consistently high complexity.
Solution Approach 2:
The robotic control system automatically calibrates and optimizes its own performance based on the specific sensor configuration being used. Through self-adjusting algorithms and adaptive learning, the system achieves high measurement accuracy without requiring complex external calibration equipment or manual tuning, reducing overall device complexity while maintaining precision.
3Measurement precision
If high-precision sensing technology is used, then measurement accuracy is improved, but robustness in dynamic environments deteriorates
Solution Approach 1:
The control system employs dynamic adaptation mechanisms that allow it to adjust its processing behavior in real-time based on environmental conditions. When operating in dynamic environments with varying sensor quality, the system can switch between different processing modes and algorithms, maintaining both accuracy and robustness by being flexible rather than fixed in its approach.
Data Source
AI summary
Systems and methods of manipulating/controlling robots. In many scenarios, data collected by a sensor (connected to a robot) may not have very high precision (e.g., a regular commercial/inexpensive sensor) or may be subjected to dynamic environmental changes. Thus, the data collected by the sensor may not indicate the parameter captured by the sensor with high accuracy. The present robotic control system is directed at such scenarios. In some embodiments, the disclosed embodiments can be used for computing a sliding velocity limit boundary for a spatial controller. In some embodiments, the disclosed embodiments can be used for teleoperation of a vehicle located in the field of view of a camera.