3D Recognition Based on Sensor Modalities for Robotic Systems: A Survey
| Autor: | Eun-Jin Kim, Jeongwon Pyo, Sang-Hyeon Bae, Sumaira Manzoor, Gun-Gyo In, Tae-Yong Kuc, Sung-Hyeon Joo |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
LiDAR
Computer science TP1-1185 Review sensors Biochemistry Analytical Chemistry Task (project management) robotic systems Human–computer interaction Humans 3D visual recognition Electrical and Electronic Engineering Instrumentation Vision Ocular sensor fusion Social robot Modalities business.industry Chemical technology Deep learning deep learning Robotics object detection Sensor fusion place recognition Atomic and Molecular Physics and Optics Variety (cybernetics) Robot 3D detection dataset Artificial intelligence autonomous vehicles business camera |
| Zdroj: | Sensors (Basel, Switzerland) Sensors, Vol 21, Iss 7120, p 7120 (2021) |
| ISSN: | 1424-8220 |
| Popis: | 3D visual recognition is a prerequisite for most autonomous robotic systems operating in the real world. It empowers robots to perform a variety of tasks, such as tracking, understanding the environment, and human–robot interaction. Autonomous robots equipped with 3D recognition capability can better perform their social roles through supportive task assistance in professional jobs and effective domestic services. For active assistance, social robots must recognize their surroundings, including objects and places to perform the task more efficiently. This article first highlights the value-centric role of social robots in society by presenting recently developed robots and describes their main features. Instigated by the recognition capability of social robots, we present the analysis of data representation methods based on sensor modalities for 3D object and place recognition using deep learning models. In this direction, we delineate the research gaps that need to be addressed, summarize 3D recognition datasets, and present performance comparisons. Finally, a discussion of future research directions concludes the article. This survey is intended to show how recent developments in 3D visual recognition based on sensor modalities using deep-learning-based approaches can lay the groundwork to inspire further research and serves as a guide to those who are interested in vision-based robotics applications. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|