Unified Robot Control for Autonomous and Teleoperation Switching
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Solution Overview
Problem
Existing robot control systems require elaborate interfaces and training methods that are costly and wear out components, limiting accessibility and effectiveness.
Innovation Solution
A control system with an autonomous and teleoperation control subsystem that receives uniform sensor data and generates identical actuator data, enabling interchangeable control between physical and simulated robots, and allowing for 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 interfaces become very elaborate and complicated requiring full operator 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 serves as a training interface that is simpler and more accessible than direct teleoperation, while maintaining operational fidelity through identical sensor data formats and actuator control structures.
Solution Approach 2:
The patent implements preliminary training in the simulated environment before deploying to the physical robot. Operators can practice and become proficient with robot control in the virtual space, which prepares them for actual teleoperation without requiring complex interfaces to be fully understood immediately.
2Reliability
If physical robots are trained by repeatedly performing tasks in the real world, then the robot learns from actual experience, but significant wear and tear occurs on robot components
Solution Approach 1:
The patent creates a simulated robot that replicates the physical robot's characteristics and behavior. Training tasks are performed on this virtual copy instead of the physical robot, allowing unlimited repetitions without mechanical wear while maintaining training effectiveness through realistic simulation physics and sensor models.
Solution Approach 2:
The simulated robot environment acts as a disposable or reusable virtual training ground that can be reset and reused indefinitely. Unlike physical components that degrade with use, the simulation can withstand unlimited training iterations without degradation, effectively serving as an inexhaustible training resource.
3Measurement precision
If physical robots are trained with elaborate teleoperation systems, then the robot can be controlled precisely, but the costs and materials become prohibitive
Solution Approach 1:
The patent creates a simulated robot that replicates the physical robot's sensor and actuator characteristics. This virtual copy enables precise control training and testing without requiring expensive physical hardware, elaborate teleoperation interfaces, or specialized training facilities, dramatically reducing overall system costs.
Solution Approach 2:
The simulation environment provides a low-cost alternative to expensive physical training setups. The virtual training system can be deployed without significant material investment, eliminating costs associated with physical robot wear, specialized facilities, and extensive teleoperation equipment while maintaining training quality.
4Adaptability or versatility
If different sensor data formats are used for autonomous and teleoperation control subsystems, then each subsystem can be optimized independently, but the control system becomes complex and difficult to manage
Solution Approach 1:
The patent implements a unified sensor data format that is used by both the autonomous control subsystem and the teleoperation control subsystem. This homogeneous data structure allows both subsystems to operate with consistent information without requiring complex format conversion or adaptation layers, simplifying the overall control system architecture.
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.