Robot Sensor Sequencing for Blind-Spot Object Detection
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Solution Overview
Problem
Existing robots face challenges in accurately identifying objects on their travel path due to blind spots created by the angle between the object and the sensor, which can be addressed by using multiple sensors to enhance detection accuracy and minimize identification time.
Innovation Solution
A robot equipped with a plurality of sensors that operate in alternating signal transmitting and receiving modes, utilizing a memory to map sensor interactions and identify the location of objects based on reflected signals, allowing for adaptive detection algorithms to quickly and accurately determine object locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single sensor is used to detect objects on the travel path, then the device complexity is reduced, but blind spots are created due to the angle between the object and sensor, reducing measurement precision
Solution Approach 1:
The detection task is segmented across multiple sensors positioned at different locations and angles on the robot. Each sensor covers a specific angular sector, and the processor integrates data from multiple sensors to achieve comprehensive coverage and eliminate blind spots, resolving the contradiction between single-sensor simplicity and multi-sensor detection accuracy.
Solution Approach 2:
The system transitions from single-point detection to multi-dimensional spatial detection by arranging sensors in different angular positions. This dimensional expansion allows the robot to detect objects from multiple angles simultaneously, eliminating blind spots while maintaining a manageable sensor configuration through systematic angular distribution.
2Measurement precision
If multiple sensors are used to eliminate blind spots, then measurement precision is improved, but the device complexity increases
Solution Approach 1:
Each sensor in the array is designed to perform the same basic detection function but from different angular perspectives. The processor universally processes signals from all sensors using the same mapping information structure, allowing the system to achieve high measurement precision while managing complexity through functional uniformity and standardized data processing.
Solution Approach 2:
The system implements feedback through the processor that receives reflection signals from multiple sensors, compares them against stored mapping information, and iteratively determines object location. This feedback mechanism allows the robot to refine its object detection accuracy by synthesizing information from multiple sensors while managing complexity through centralized intelligent processing.
3Reliability
If sensors operate continuously in signal transmitting mode, then detection coverage is maximized, but energy consumption increases
Solution Approach 1:
Sensors operate in periodic cycles, alternating between signal transmitting mode and signal receiving mode. During the transmitting phase, sensors emit detection signals; during the receiving phase, they listen for reflections. This periodic operation ensures reliable object detection while significantly reducing energy consumption compared to continuous transmission, as sensors spend most time in the lower-power receiving state.
Solution Approach 2:
The system performs preliminary action by pre-storing mapping information that correlates sensor signals with object locations. This pre-computed mapping allows the processor to quickly determine object positions from received signals without requiring continuous active transmission, enabling reliable detection with intermittent sensor activation and reduced energy consumption.
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 enables the robot to efficiently and accurately identify object locations, reducing detection time and enhancing performance by optimizing sensor usage and travel path navigation.
Implementation Method 1
identify, based on the first signal being reflected from the object during a second time period after elapse of the first time period and received in at least one sensor operating in a signal receiving mode
Data Source
AI summary
A robot, includes: a driver; a plurality of sensors; a memory; and at least one processor configured to transmit a first signal for identifying a presence or absence of an object within a sensing area of the plurality of sensors through a first sensor operating in the signal transmitting mode from among the plurality of sensors during a first time period, identify, a second sensor to transmit a second signal during a third time period after elapse of the second time period from among the plurality of sensors, transmit the second signal by operating the identified second sensor in the signal transmitting mode, identify a location of the object based on whether a second reflection signal corresponding to the second signal is received at the second sensor, and control the driver to travel by avoiding the object based on the identified location of the object.