Mobile Robot Volumetric Point Cloud Navigation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current mobile robots lack effective navigation and object detection capabilities, particularly in dynamic environments, due to limitations in sensing technologies and processing power, which hinders their ability to efficiently interact with humans and navigate complex spaces.
Innovation Solution
A mobile robot equipped with a high-processing-capability controller, a volumetric point cloud imaging device, and a holonomic drive system, capable of emitting and processing three-dimensional depth images, speckle patterns, and ambient illumination, allowing for precise object detection and navigation by determining object locations and issuing drive commands based on received image data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If mobile robots use traditional sensing technologies and processing power, then device complexity is reduced, but navigation and object detection capabilities are insufficient
Solution Approach 1:
The patent combines multiple sensing modalities (volumetric point cloud imaging, time-of-flight measurement, speckle pattern analysis, ambient illumination sensing) into a unified sensor system. This integration allows the robot to achieve superior object detection and navigation capabilities by merging the strengths of different sensing technologies rather than relying on a single sensor type.
Solution Approach 2:
The sensor system is designed to perform multiple functions simultaneously: it captures volumetric point cloud data for 3D mapping, measures time-of-flight for depth estimation, analyzes speckle patterns for surface characterization, and senses ambient illumination for environmental context. This multi-functionality allows a single integrated system to replace multiple specialized sensors, improving capabilities while managing complexity.
2Measurement precision
If mobile robots use volumetric point cloud imaging and high-processing controllers, then navigation accuracy is improved, but energy consumption increases
Solution Approach 1:
The controller operates in periodic cycles, alternating between high-processing modes for accurate navigation calculations and lower-power states for data acquisition. The system periodically updates the volumetric point cloud model and processes speckle pattern data only when needed for navigation decisions, rather than continuously at full processing capacity, thereby reducing overall energy consumption while maintaining navigation accuracy.
3Measurement precision
If mobile robots process three-dimensional depth images and speckle patterns in real-time, then object detection precision is improved, but processing time increases
Solution Approach 1:
The system performs preliminary processing of the volumetric point cloud data and speckle pattern information to create pre-computed navigation models and object signatures. By preparing these data structures in advance during periods of lower computational demand, the system reduces the processing time required during critical navigation and object detection moments, achieving both high precision and timely responses.
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
Enables the robot to accurately navigate and interact with humans by classifying objects and free spaces, avoiding obstacles, and following individuals, enhancing its operational efficiency and safety in various environments.
Implementation Method 1
The imaging device determines a time-of-flight between emitting the light and receiving reflected light from the scene. The controller uses the time-of-flight for determining a distance to the reflecting surfaces of the object.
Implementation Method 2
The imaging device includes a light source for emitting light and an imager for receiving reflections of the emitted light from the scene.
Implementation Method 3
The imaging device may include a speckle emitter emitting a speckle pattern of light onto a scene along a drive direction of the robot and an imager receiving reflections of the speckle pattern from the object in the scene.
Data Source
AI summary
A mobile robot that includes a drive system, a controller in communication with the drive system, and a volumetric point cloud imaging device supported above the drive system at a height of greater than about one feet above the ground and directed to be capable of obtaining a point cloud from a volume of space that includes a floor plane in a direction of movement of the mobile robot. The controller receives point cloud signals from the imaging device and issues drive commands to the drive system based at least in part on the received point cloud signals.