Robot Sensor-Actuator Matching for Low-Wear Training
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Solution Overview
Problem
Existing robot technologies face challenges in the field for technologies technologies face challenges in controlling robots, including the need for elaborate teleoperation systems that require full pilot attention, significant wear and tear during training, and high costs when success is not guaranteed.
Innovation Solution
A control system that integrates an autonomous control subsystem and a teleoperation control subsystem, allowing interchangeable control between physical and simulated robots, with identical sensor and actuator data types, sizes, and frequencies, enabling fully or semi-autonomous operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If teleoperation systems are used to control robots, then human operators can directly control robot actions, but the systems require very elaborate and complicated interfaces comprising sophisticated sensors and equipment that require full pilot attention
Solution Approach 1:
The patent creates a simulated robot that copies the physical robot's appearance, sensors, and actuators in a virtual environment. This simulation allows operators to practice and train without needing complex teleoperation hardware, reducing the barrier to entry while maintaining control capability.
Solution Approach 2:
The system enables preliminary training and task rehearsal in the simulated environment before deploying to the physical robot. Operators can practice control procedures, test scenarios, and become familiar with robot operations in advance, reducing the need for complex real-time teleoperation interfaces during actual deployment.
2Productivity
If physical robots are trained by repeatedly performing tasks in the real world, then the robot learns to perform work, but significant wear and tear occurs on the robot components
Solution Approach 1:
The patent creates a simulated robot that replicates the physical robot's characteristics in a virtual environment. Training tasks are performed on the simulated robot, allowing unlimited repetitions without physical wear. The simulation maintains realistic physics and sensor feedback to preserve training effectiveness while eliminating component degradation.
Solution Approach 2:
The simulated robot acts as a disposable or reusable virtual counterpart that can be repeatedly used for training without degradation. Unlike the expensive physical robot, the simulation can endure infinite training cycles, task repetitions, and experimental scenarios without any wear, tear, or maintenance requirements.
3Reliability
If physical robots are trained with elaborate teleoperation systems, then the robot can be controlled, but the costs and materials associated with training become prohibitive when success is not guaranteed
Solution Approach 1:
The simulated robot provides a cost-free or low-cost virtual counterpart that replicates the physical robot's control characteristics. Multiple training scenarios can be executed in the simulation without consuming physical resources, reducing training costs while maintaining control capability. Failures in simulation do not incur material costs or equipment damage.
Solution Approach 2:
The system enables preliminary testing and validation of control strategies in the simulated environment before executing them on the physical robot. This preliminary action allows operators to refine control algorithms, test edge cases, and validate procedures without risking expensive physical hardware or incurring high training costs, ensuring better success rates when deploying to the real robot.
Data Source
AI summary
Provided herein is a control system and methods thereof for controlling operation of a robot. The control system comprises: a robot, including a plurality of sensors wherein each generating a stream of raw sensor data having a data type, size, and frequency, and a plurality of actuators cause movement of the robot; an autonomous control subsystem configured to receive the sensor data and output autonomous actuator data; and a teleoperation control subsystem configured to receive the sensor data, transmit the sensor data to a human operator, and output teleoperation actuator control signals, wherein the autonomous control subsystem and the teleoperation control subsystem receive, from the robot, sensor data having the same data type, size, and frequency, and wherein the autonomous actuator data and the teleoperation actuator data have the same data type, size, and frequency; and a control-determining subsystem configured to switch between autonomous and teleoperation control.