Monocular Depth Estimation for Sensor-Free Robotic Motion Detection

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Solution Overview

Problem

Robotic devices face challenges in perceiving the surrounding environment due to limited depth and motion information from monocular cameras, necessitating additional costly sensors like LiDAR or radar.

Innovation Solution

A motion system that utilizes monocular depth estimation to derive depth maps from images, processing them with machine learning or heuristic models to determine motion information without additional sensors.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of manufacture

If monocular cameras are used to acquire information about the surroundings, then cost is reduced, but depth information and motion information are not explicitly provided

Engineering Contradiction:

ImprovecostVSAvoiddepth information

Core Design Contradiction:

Ease of manufactureVSLoss of information

Solution Approach 1:

The patent introduces depth estimation algorithms as an intermediary processing step that transforms monocular image data into depth information. The system uses machine learning models or heuristic algorithms to estimate depth from single-camera images, effectively creating depth information without adding depth-sensing hardware.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent replaces mechanical/optical depth-sensing systems (such as LiDAR, stereo cameras, or radar) with computational methods. Instead of using additional physical sensors to capture depth, the system substitutes computational depth estimation algorithms that process monocular images to derive depth information.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Measurement precision

If additional sensors like LiDAR or radar are implemented to acquire depth and motion information, then measurement precision is improved, but device complexity and cost increase

Engineering Contradiction:

Improvedepth informationVSAvoidsensor modalities

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent makes the monocular camera system multi-functional by enabling it to provide not only standard image data but also estimated depth information and motion information through computational processing. The same hardware component performs multiple sensing functions through algorithmic enhancement.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent creates computational copies of depth and motion information that would traditionally require separate physical sensors. By generating depth maps and motion estimates from monocular images, the system replicates the functionality of LiDAR and radar without duplicating the hardware.

Inventive Principle:

Principle #26Copying

Data Source

PatentUS20250245840A1Determining motion using monocular depth estimation

Publication Date: 2025.07.31 TOYOTA RESEARCH INSTITUTE INC

AI summary

Systems, methods, and other embodiments described herein relate to determining motion from images with the use of monocular depth estimation. In one embodiment, a method includes acquiring images depicting surrounding objects present in an environment. The method includes generating depth maps for the images according to a depth model that performs monocular depth estimation. The method includes generating an indicator about motion associated with the surrounding objects according to the depth maps. The method includes providing the indicator about motion.