Smartphone-Based Robot Navigation With Low-Cost Perception
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Solution Overview
Problem
Current robots are prohibitively expensive due to the need for expensive computational platforms and high-quality sensors, making them inaccessible for various applications.
Innovation Solution
Utilizing a mobile communication terminal with integrated sensors and processors to equip robots with robust perception and logic control, reducing the cost by leveraging existing processing ability and sensor suites, and implementing a custom communication protocol for efficient data transfer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional robots use dedicated computational platforms and high-quality sensors, then perception accuracy and control reliability are improved, but manufacturing cost increases significantly
Solution Approach 1:
The patent applies universality by using a mobile communication terminal (smartphone) to perform multiple functions: it serves as the computational platform for processing sensor data, the control system for generating navigation instructions, and even provides some sensing capabilities through its own sensors. This multi-functional approach eliminates the need for separate dedicated robot computers and high-cost sensors, thereby reducing manufacturing costs while maintaining reliable perception and control
Solution Approach 2:
The patent uses copying by leveraging the sensor suite already present in the mobile communication terminal (camera, microphone, accelerometer, GPS, etc.) instead of installing separate robot-specific sensors. The terminal's existing sensors are copied/repurposed for robot navigation tasks, significantly reducing the cost of sensor hardware while providing sufficient perception capabilities for the robot's operational needs
2Adaptability or versatility
If robots are equipped with multiple sensors and processors for environment perception, then navigation capability is improved, but device complexity increases
Solution Approach 1:
The mobile communication terminal serves as a universal platform that combines computational power, sensor suite, and communication capabilities in one device. It processes data from both its own sensors and the robot's simple sensors, generates navigation instructions, and communicates with the robot through a standardized interface, thereby improving navigation capability while avoiding the complexity of multiple separate systems
Solution Approach 2:
The mobile communication terminal acts as an intermediary between the simple robot hardware and the complex tasks of environment perception and navigation. It receives simple sensor data from the robot, processes this data along with data from its own sensors using its sophisticated processors, generates complex navigation instructions, and sends them back to the robot, thereby mediating the complexity rather than requiring the robot itself to be complex
3Productivity
If a custom communication protocol is implemented for data transfer between mobile terminal and robot, then communication efficiency is improved, but implementation complexity increases
Solution Approach 1:
The patent replaces complex mechanical/protocol-based communication systems with a simplified digital communication approach using existing mobile terminal interfaces (USB, Bluetooth, Wi-Fi). Instead of implementing complex custom communication protocols at the hardware level, the solution uses software-based communication over standard interfaces, thereby improving communication efficiency while reducing implementation complexity through the use of established communication stacks
Data Source
AI summary
A mobile communication terminal device may include one or more image sensors, configured to generate image sensor data representing an environment of the mobile communication terminal device; one or more processors, configured to receive the image sensor data from the one or more image sensors; implement at least one artificial neural network to receive the image sensor data as an artificial neural network input and output an artificial neural network output representing a detected environment parameter of the environment of the mobile communication terminal; determine a navigation instruction based on the artificial neural network output; and send a signal representing the navigation instruction to a robot terminal via a communication interface.