Special Issue on Ambient Understanding for Mobile Autonomous Robots

Journal of Ambient Intelligence and Humanized Computing (AIHC)

Journal Impact Factor (2020): 7.104 (ISSN: 1868-5137)

Website: https://www.springer.com/journal/12652/updates/19709550

Submission Deadline: 28th February 2022

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=== Call for papers ===

In recent years, the combination of robotics and artificial intelligence arose outstanding developments in the fields of cognitive robotics and human robot interaction. Nowadays several academic and industrial research groups are engaged in the design of intelligent robots able to act autonomously, by means of advanced deep learning algorithms used for the analysis of data acquired from heterogeneous sensors (camera, 3D camera, stereo camera, microphone, LIDAR, sonar etc.), for ambient understanding (people, objects, scenes) and for dynamically adapting the interaction with humans and environment.

Despite the recent deep learning achievements and the impressive advances in technology for intelligent robot systems, there are still several challenges to be addressed in computer vision, audio analysis, sensor fusion, autonomous navigation methods and human robot interaction. Such challenges arise from the inherent difficulty of designing algorithms that are effective in the complex real world, but are also due to the acquisition of low quality or corrupted images, noisy audio and inaccurate data from environmental sensors, and to the necessity to process large amounts of operations in real-time.

The aim of the special issue is to provide a collection of innovative algorithms, theories and applications related to all the aspects of perception, reasoning and navigation of a mobile autonomous robot, with contributions from both academia and industry. Even the submission of datasets and benchmarks collected in real challenging conditions or methods optimized for real-time perception and reasoning are encouraged.

Topics of interest are, but not limited to:

• Face Analysis (Detection, Recognition, Re-Identification, Gender, Age, Ethnicity, Emotion)

• People detection

• 2D and 3D object detection and recognition for ambient understanding and reconstruction

• 6D Pose Estimation

• Gesture and action recognition

• Voice and audio event detection and localization

• Speech Analysis for human-robot interaction (Speaker Recognition, Gender, Age, Language, Emotion, Speech to text, Natural Language Processing)

• Multi-modal perception for human-robot interaction and autonomous navigation

• Ambient understanding for SLAM, dynamic motion planning and autonomous navigation

• Reinforcement learning for cognitive robotics

• Datasets and benchmarks in the wild

• Software optimization for real-time perception, reasoning and navigation

• Embedded systems for cognitive robotics

• Algorithms for autonomous car driving

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=== Guest editors ===

Antonio Greco (Università degli Studi di Salerno, Italy)

Mario Vento (Università degli Studi di Salerno, Italy)

Sean Ryan Fanello (Google, USA)

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Antonio Greco, Ph. D.

Assistant Professor

Dept. of Computer Engineering, Electrical Engineering and Applied Mathematics (DIEM)

Laboratory of Intelligent Machines for the Analysis of Videos, Images and Audio (MIVIA)

University of Salerno, Via Giovanni Paolo II, 132 84084 – Fisciano (SA) Italy

Phone:+39 089 963006

Web:    

http://docenti.unisa.it/antonio.greco

http://mivia.unisa.it/people/greco/

Skype: antonio.greco17589