Haptic Photogrammetry in Robots for Accurate Object and Surface Profiling
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Solution Overview
Problem
Robots operating in environments face suboptimal performance due to incomplete environment models, which lack comprehensive sensory data, leading to inadequate interaction with objects and surfaces.
Innovation Solution
A robot system equipped with haptic sensors and processors that access and refine environment models using haptic and visual data, allowing for accurate object identification and surface profiling, enabling improved control and interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If robots use basic environment models for operation, then device complexity is reduced, but measurement precision and interaction accuracy deteriorate
Solution Approach 1:
The environment model is segmented into multiple sensory modalities including haptic profiles, visual profiles, and tactile characteristics. Each modality is independently captured by specialized sensors (haptic sensors, cameras, microphones) and processed separately, then integrated to form a comprehensive environment model. This segmentation allows high measurement precision through specialized sensing while managing complexity through modular architecture.
Solution Approach 2:
A processor acts as an intermediary that receives raw sensory data from multiple sensors, processes and integrates this data into structured environment models, and provides refined information to the robot control system. This intermediary layer abstracts the complexity of multi-sensor integration while delivering high-precision environmental representations for accurate robot interaction.
2Loss of information
If robots collect comprehensive haptic and visual data, then information completeness improves, but loss of time in data processing increases
Solution Approach 1:
Haptic profiles and visual profiles of objects are pre-characterized and stored in databases before robot operation. When the robot encounters an object, it performs rapid matching between sensor readings and pre-stored profiles, avoiding time-consuming real-time analysis. This preliminary action captures comprehensive environmental information in advance while enabling fast processing during operation.
Solution Approach 2:
The system continuously refines environment models by comparing sensor feedback with existing models and updating discrepancies. Haptic sensors provide real-time feedback on object properties, which is integrated with visual data to progressively improve environmental understanding. This feedback loop maintains information completeness while optimizing processing efficiency through iterative refinement rather than exhaustive analysis.
3Adaptability or versatility
If robots use multiple sensors for environment modeling, then adaptability to different objects improves, but device complexity increases
Solution Approach 1:
The robot system employs a universal environment model framework that integrates multiple sensory modalities (haptic, visual, acoustic) into a unified representation structure. This multi-functional model can represent diverse object types and environmental conditions through consistent data structures, allowing the same system to adapt to various objects without requiring separate specialized systems for each sensor type or object category.
Solution Approach 2:
The environment model functions as a composite information structure that combines data from different sensory sources (haptic profiles, visual profiles, tactile characteristics) into an integrated representation. This composite model leverages the complementary strengths of each sensor type, achieving versatile object recognition and interaction capability while managing complexity through unified data integration rather than separate processing systems.
Data Source
AI summary
Robots, robot systems, and methods for operating the same based on environment models including haptic data are described. An environment model which includes representations of objects in an environment is accessed, and a robot system is controlled based on the environment model. The environment model incudes haptic data, which provides more effective control of the robot. The environment model is populated based on visual profiles, haptic profiles, and/or other data profiles for objects or features retrieved from respective databases. Identification of objects or features can be based on cross-referencing between visual and haptic profiles, to populate the environment model with data not directly collected by a robot which is populating the model, or data not directly collected from the actual objects or features in the environment.