Virtual Probe Sensor Emulation for Robot Simulation
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Solution Overview
Problem
The design and testing of robots are costly and time-consuming due to the need for physical buildouts and multiple iterations, particularly in incorporating perception systems like visual and LiDAR sensors, which require expensive components and extensive testing cycles.
Innovation Solution
A computer-implemented method for emulating a probe sensor in a virtual environment, where a cloud server initializes a robot simulation session, instantiating virtual objects and robots with virtual sensors that emit rays stochastically selected in direction, capturing data by raytracing to generate a perception stack output, allowing for efficient simulation and testing of robot designs without physical prototypes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physical robot buildouts with real sensors are used for design and testing, then measurement precision and reliability are improved, but cost and time consumption increase significantly
Solution Approach 1:
The patent creates virtual copies of physical sensors (camera, LiDAR, microphone) that operate within a simulated environment. These virtual sensors replicate the functionality and data output of real sensors, allowing designers to test robot perception systems without physical prototypes. The virtual camera captures images, the virtual LiDAR generates depth maps, and the virtual microphone records audio, all within the simulation, eliminating the need for expensive physical buildouts during the design phase.
Solution Approach 2:
The patent introduces a simulation environment as an intermediary between the designer and the physical robot. This virtual environment mediates the testing process by providing a controlled digital space where sensor behaviors can be observed and evaluated before physical implementation. The simulation acts as a bridge, allowing virtual sensor data to inform real-world design decisions without requiring direct interaction with physical components during iteration cycles.
2Reliability
If physical robot components are built and tested iteratively, then design reliability is improved, but cost and time requirements worsen
Solution Approach 1:
The patent enables preliminary testing and validation of robot designs in the virtual environment before physical manufacturing. Designers can configure virtual sensors, define their parameters and behaviors, and test various robot designs and sensor configurations in the simulation. This preliminary action allows multiple design iterations to be evaluated digitally, ensuring design reliability is established before committing to physical production, thereby simplifying the overall manufacturing process.
3Measurement precision
If multiple physical sensor types are integrated for comprehensive perception, then measurement capability is improved, but device complexity and cost increase
Solution Approach 1:
The patent implements a universal simulation environment that can host multiple types of virtual sensors (camera, LiDAR, microphone) with consistent interfaces and integration methods. Each virtual sensor type maintains its specific measurement capabilities while adhering to a unified framework for configuration, data output, and interaction with the simulated robot and environment. This multi-functional approach allows comprehensive perception testing without the complexity of integrating diverse physical sensor systems.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces costs and time by enabling effective simulation and testing of robot designs in a virtual environment, allowing for the optimization of robot designs and perception systems without the need for physical prototypes, thereby streamlining the design and testing process.
Implementation Method 1
Capturing the data perceived by the virtual sensor includes emitting a plurality of rays by the virtual sensor, each ray transmitted in a stochastically selected direction, and capturing the data perceived by each ray by raytracing each ray to determine an object in the virtual environment on which the ray is incident
Data Source
AI summary
Techniques are described to implement a probe sensor that improves data capture and data analysis. A probe sensor can be emulated in a virtual environment. A robot simulation session is initialized. The session includes a virtual environment with several objects and a set of robots. Each robot has a virtual sensor. A separate client controls each robot. Data perceived by the virtual sensor is provided to the client for controlling the robot. To capture the data the virtual sensor emits a plurality of rays, each ray transmitted in a stochastically selected direction, and performs raytracing to determine an object(s) in the virtual environment on which each ray is incident. The stochastic data capture can also be performed by a sensor in a real world scenario. Further, in some cases, the data captured by a sensor is stochastically sampled to improve the computing.