Hide-And-Seek Robot Blind Spot Detection Using User Movement Tracing
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Solution Overview
Problem
Conventional robots face difficulties in identifying the exact blind spot where a user, particularly a young child, is hiding during games like hide-and-seek, as they lack mechanisms to access and recognize spaces like those formed between a door and a wall or under blankets, leading to random selections that may not accurately pinpoint the hiding location.
Innovation Solution
A robot equipped with a movement mechanism, sensors for detecting electromagnetic or sound waves, a microphone for sound acquisition, and a processor that uses tables to determine the region with the fewest blind spots and traces the user's movement locus to identify likely hiding spots, ensuring accurate detection and fair gameplay by potentially losing intentionally.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the robot uses conventional blind spot identification methods, then it can identify blind spots in open spaces, but it cannot accurately identify blind spots where users are hiding in confined spaces
Solution Approach 1:
The robot segments the detection process into multiple phases: initial position selection using the first table (region-blind spot count), user movement tracking, and final blind spot identification using the second table (blind spot-position mapping). This segmented approach allows the robot to adapt to different detection stages and accurately identify hiding spots in confined spaces that conventional single-phase methods miss.
Solution Approach 2:
The robot performs preliminary actions by pre-mapping the environment to create two tables: the first table storing region-blind spot count associations, and the second table storing blind spot-position associations. These pre-computed data structures enable the robot to quickly and accurately identify hiding spots during gameplay without requiring complex real-time analysis of confined spaces.
2Reliability
If the robot searches the entire space to find the user, then it can ensure complete coverage, but it increases the time required to locate the user
Solution Approach 1:
The robot performs preliminary mapping of the entire space to identify all blind spots and their positions, storing this information in the second table before gameplay begins. During the actual search, the robot only needs to query this pre-computed data structure based on the user's movement locus, dramatically reducing search time while maintaining complete coverage reliability.
Solution Approach 2:
The patent replaces the mechanical brute-force search method with an information-based approach. Instead of physically scanning the entire space during gameplay, the robot substitutes the mechanical search with computational queries to the pre-computed second table, using the user's movement locus to quickly identify the hiding blind spot without time-consuming physical inspection of all areas.
3Measurement precision
If the robot always wins at hide-and-seek by finding the user, then it demonstrates superior detection capability, but it reduces user engagement and game fairness
Solution Approach 1:
The robot dynamically adjusts its detection strategy based on gameplay requirements. It can switch between accurate detection mode (using the full two-table methodology to find the user) and fair play mode (intentionally losing by selecting a different blind spot). This dynamic adaptability allows the robot to maintain superior detection capability while also providing engaging, fair gameplay experiences that keep users interested.
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
The robot effectively identifies blind spots where the user is likely hiding, ensuring fair gameplay and improving the accuracy of hiding spot detection, even in areas conventional robots cannot access, by using sensor data and table associations to guide its movements.
Implementation Method 1
a sensor that detects an electromagnetic wave or sound wave reflected by an object
Implementation Method 2
a microphone that acquires a sound of an area around the apparatus
Data Source
AI summary
An apparatus includes a movement mechanism, a sensor, a microphone, a speaker, a processor and a memory. The processor selects a target region, controls the movement mechanism to cause the apparatus to move to the target region, and causes a speaker to output a first sound. When counting a predetermined number, the processor causes the sensor to trace a movement locus of a user. In a case where the processor has determined that an acquired sound contains a predetermined speech, the processor controls the movement mechanism to cause the apparatus to move through a predetermined space. When the processor has determined that the apparatus is not to intentionally lose in a game of hide-and-seek, the processor controls the movement mechanism to cause the apparatus to move to a target blind spot within the predetermined space, and causes the speaker to output a second sound.