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New Metrics for Industrial Depth Sensors Evaluation for Precise Robotic Applications

Konrad P Cop, Arne Peters, Bare Luka Žagar, Daniel Hettegger, Alois Knoll

Year
2021
Citations
28

Abstract

Precise perception is one of the key enablers of autonomous robotic operations. The right selection of sensors significantly influences the overall performance of the system. This paper provides a systematic approach for evaluation of various sensors available on the market. The main focus is to assess the performance in use cases of short to medium distance operations, especially relevant for precise manipulation and/or quality control. The evaluation is based solely on depth data (point clouds). We use six metrics to evaluate the sensors and propose a novel approach for low-cost fabrication of benchmark targets. The evaluation experiments are conducted on different materials to simulate various industrial environments. Our results provide a qualitative and quantitative comparison of different characteristics of various sensors and can be used to select an appropriate device for specific conditions.

Keywords

Computer scienceBenchmark (surveying)Key (lock)Focus (optics)Point cloudQuality (philosophy)Point (geometry)Real-time computingArtificial intelligenceHuman–computer interaction

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