Autonomous Mobile Robotics
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".
Deadline for manuscript submissions: closed (31 December 2019) | Viewed by 3951
Special Issue Editors
Interests: machine learning; multi-sensor fusion; vision for robotics; autonomous mobile robotics
Special Issues, Collections and Topics in MDPI journals
Interests: multi-modal perception; multi-sensor data fusion; computer vision; intelligent transportation systems; mobile robotics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Autonomous and self-navigating robots have been rising in popularity due to a push for a more technologically aided future. The applications of autonomous robots are vast and span many different fields as evidenced by recent developments such as smart mobility for intelligent transport systems, advanced manufacturing technologies for future industry, mini-UAVs for missions such as monitoring large infrastructures and search and rescue applications, and applications in the fields of agriculture and ocean engineering. These autonomous robots, often heterogeneous in terms of shape, energy autonomy, and computing capabilities, are increasingly evolving in open, complex, dynamic environments, and they are interacting with humans. In addition, the convergence of massive databases, important embedded computing capabilities and new paradigms of artificial intelligence have given robotics systems greater autonomy and reasoning capabilities.
This Special Issue aims to collect the most recent studies and applications on deep learning techniques and mobile robotics. Topics will include, but are not strictly limited to
- Advanced machine learning techniques for SLAM;
- Deep fusion architectures for robotic perception sensors;
- Emergent sensing capabilities for mobile robotics;
- Deep reinforcement learning for mobile robots' navigation;
- Dynamic scene analysis and multi-object detection and tracking;
- Real-time inference and hardware implementation;
- Data-driven navigation and control;
- Autonomous mobile robots’ applications on ground, air, and water…
Prof. Vincent Frémont
Dr. Sergio Alberto Rodriguez Florez
Guest Editors
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Keywords
- Advanced machine learning techniques for SLAM;
- Deep fusion architectures for robotic perception sensors;
- Emergent sensing capabilities for mobile robotics;
- Deep reinforcement learning for mobile robots' navigation;
- Dynamic scene analysis and multi-object detection and tracking;
- Real-time inference and hardware implementation;
- Data-driven navigation and control;
- Autonomous mobile robots’ applications on ground, air, and water…
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