Robot navigational sensor system
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Solution Overview
Problem
Autonomous robotic vacuum cleaners face challenges in accurately detecting small, dark-colored obstacles such as chair and table legs, which can lead to collisions and damage, as existing detection methods are not effective in resolving the position of these objects with sufficient precision.
Innovation Solution
The implementation of a proximity sensor system with a horizontally-oriented receiver and two emitters, where the receiver is positioned between the emitters and angled to intersect their beams, creating a bounded detection volume that allows for accurate detection of small, dark-colored objects by generating a signal from reflected radiation, enabling the robot to slow down and avoid collisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional sensor systems are used, then the robot can detect obstacles, but it cannot accurately detect small, dark-colored obstacles such as chair and table legs
Solution Approach 1:
The sensor system divides the detection task into multiple independent emitter-receiver pairs, each responsible for specific spatial zones. This segmentation allows the system to detect small, dark obstacles by combining information from multiple discrete sensor units, improving measurement precision for challenging objects
Solution Approach 2:
Different emitter-receiver pairs are positioned with specific local orientations and detection zones tailored to detect small, dark obstacles in particular areas. The receiver is positioned below the emitter plane and angled to create overlapping detection volumes that specifically target regions where small obstacles are likely to be detected
2Reliability
If the robot slows down to avoid collisions, then collision damage is prevented, but cleaning productivity decreases
Solution Approach 1:
The sensor system performs preliminary detection of small, dark obstacles before the robot reaches them, allowing the control system to plan avoidance maneuvers in advance. This early detection enables the robot to maintain higher speeds while still preventing collisions, as the avoidance action is initiated before the obstacle becomes an immediate threat
Solution Approach 2:
The sensor system continuously provides feedback about obstacle positions and distances, allowing the control system to dynamically adjust robot speed and trajectory. This closed-loop control enables the robot to maintain high productivity by only slowing down when and where necessary to avoid detected obstacles
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 solution enables the robot to detect small, dark-colored obstacles with greater accuracy, preventing damage and improving navigation by allowing the robot to maneuver around them effectively, while also being compact and suitable for robots with a flat front profile.
Implementation Method 1
The receiver is configured to generate a signal in response to receiving reflected radiation produced by the first and second emitters as the first and second emitters are activated sequentially
Data Source
AI summary
An autonomous robot comprises a robot body, a drive configured to propel the robot, a sensor system disposed on the robot body, and a navigation controller circuit in communication with the drive and the sensor system. The sensor system comprises at least one proximity sensor comprising a sensor body, and a first emitter, a second emitter and a receiver housed by the sensor body, wherein the receiver detects objects in a bounded detection volume of the receiver field of view aimed outward and downward beyond a periphery of the robot body. The receiver is disposed above and between the first and second emitters, the emitters having a twice-reshaped emission beams angled upward to intersect the receiver field of view at a fixed range of distances from the periphery of the robot body to define the bounded detection volume.