Robotic Simulation Control With Real-State Validation
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Solution Overview
Problem
Existing robotic control systems rely on simulated training data but do not actively utilize robotic simulators during real-world robotic control, leading to inefficiencies and potential suboptimal action sequences.
Innovation Solution
Implement a robotic simulator that reflects the real-world environment using sensor-based observations, determines robotic action sequences, and compares simulated and real-world data to ensure accurate and efficient robotic control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If robotic simulators are used to generate training data for machine learning models, then the models can be trained for robotic control tasks, but the simulators are not actively utilized during real-world robotic control operations
Solution Approach 1:
The system performs preliminary action by simulating robotic actions in a virtual environment before executing them in the real world. The robotic simulator generates simulated state data instances that predict environmental and robot state outcomes, which are then compared with actual real-world state data to validate action sequences before full implementation.
Solution Approach 2:
The system creates a virtual copy of the real-world environment and robot in the simulator. This digital twin approach allows the robotic simulator to model the robot's behavior and environmental interactions, generating predicted state data that mirrors what would occur in the physical world, enabling validation without physical trial-and-error.
2Reliability
If multiple candidate sequences of robotic actions are evaluated in simulation, then the most effective sequence can be selected, but computational resources and time are consumed
Solution Approach 1:
The system applies partial action by evaluating candidate action sequences to a limited depth in simulation rather than completing full execution. The robotic simulator generates simulated state data instances for each candidate sequence and compares them with real state data instances, stopping evaluation when sufficient confidence is achieved or a threshold is met, rather than exhaustively testing all possibilities.
Solution Approach 2:
The system changes parameters by adjusting the frequency of comparisons between simulated and real state data instances. The controller can dynamically control how often simulated state data is compared with real state data, allowing flexible trade-offs between validation thoroughness and computational time consumption based on operational requirements.
3Reliability
If simulated state data instances are compared with real state data instances at every step, then environmental consistency can be ensured, but computational overhead increases
Solution Approach 1:
The system implements periodic action by comparing simulated state data instances with real state data instances at specific intervals or frequency rather than continuously at every single time step. The controller determines the comparison frequency based on operational needs, allowing periodic validation of environmental consistency while reducing continuous computational overhead.
Data Source
AI summary
Active utilization of a robotic simulator in control of one or more real world robots. A simulated environment of the robotic simulator can be configured to reflect a real world environment in which a real robot is currently disposed, or will be disposed. The robotic simulator can then be used to determine a sequence of robotic actions for use by the real world robot(s) in performing at least part of a robotic task. The sequence of robotic actions can be applied, to a simulated robot of the robotic simulator, to generate a sequence of anticipated simulated state data instances. The real robot can be controlled to implement the sequence of robotic actions. The implementation of one or more of the robotic actions can be contingent on a real state data instance having at least a threshold degree of similarity to a corresponding one of the anticipated simulated state data instances.