Modular Robot Sensors for Detailed Mapping and Fast Upgrades
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Solution Overview
Problem
Existing robots are limited in their ability to enhance performance and mapping capabilities without costly and inefficient hardware upgrades, particularly due to defects or the need for environment-specific tasks.
Innovation Solution
The use of modular devices that can be easily coupled and decoupled from robots, providing additional sensory modules such as cameras, LiDAR sensors, and light-detecting and ranging components to enhance mapping and task performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If additional sensory modules are integrated into robots to enhance mapping and task performance, then the robot's capability and productivity are improved, but the device complexity and cost increase
Solution Approach 1:
The patent divides the robotic system into modular components where sensory modules can be independently attached and detached. Each sensory module (camera, LiDAR, microphones) functions as a separate unit that interfaces with the robot through standardized connection protocols, allowing the system to scale complexity only when needed rather than requiring a permanently complex integrated system.
Solution Approach 2:
The patent creates a universal interface system that allows a single robot platform to perform multiple functions by attaching different sensory modules. The standardized connection protocol and common processing framework enable the same robot base to work with various sensor types (visual, auditory, depth sensing) without requiring separate hardware designs for each function.
2Measurement precision
If sensory modules are permanently integrated into robots, then mapping precision and navigation accuracy are improved, but the ease of operation and adaptability decrease
Solution Approach 1:
The patent implements a dynamic configuration system where the robot's sensory capabilities can be changed based on environmental requirements. Users can attach different sensory modules for different tasks (e.g., adding depth cameras for narrow corridors, adding microphones for acoustic mapping) and detach them when no longer needed, making the system adaptable to varying operational contexts while maintaining high precision when equipped.
Solution Approach 2:
The patent introduces an intermediary processing layer that mediates between various sensory modules and the robot's navigation system. This intermediate software framework standardizes data from different sensor types and integrates them uniformly, allowing precise mapping functionality to be achieved through multiple different sensor configurations rather than requiring a single fixed sensor suite.
3Productivity
If hardware upgrades are performed on existing robots to improve performance, then the robot's capability is enhanced, but the loss of time and operational disruption increase
Solution Approach 1:
The patent extracts the sensory modules from permanent integration and makes them separable components. This allows the sensory upgrading process to be reduced to simply detaching old modules and attaching new ones, rather than requiring complex hardware modifications, disassembly, or system reconfiguration that would consume significant time and disrupt operations.
4Ease of operation
If standardized connection interfaces are implemented for sensory modules, then the ease of operation and modularity are improved, but the manufacturing precision and customization options decrease
Solution Approach 1:
The patent employs parameter changes in the connection interface design, using magnetic coupling with specific strength parameters, spring-loaded electrical contacts with defined pressure parameters, and alignment features with tolerance parameters. These controlled parameter specifications enable easy attachment through simple actions while automatically ensuring precise mechanical and electrical connections without requiring manual adjustment or high-precision manual assembly.
Data Source
AI summary
Systems and methods for enhancing task performance and computer readable maps produced by robots using modular sensors is disclosed herein. According to at least one non-limiting exemplary embodiment, robots may perform a first set of tasks, wherein coupling one or more modular sensors to the robots may configure a robot to perform a second set of tasks, the second set of tasks includes the first set of tasks and at least one additional task.