Autonomous Robots for Inspection and Maintenance
A special issue of Robotics (ISSN 2218-6581). This special issue belongs to the section "Industrial Robots and Automation".
Deadline for manuscript submissions: closed (31 August 2022) | Viewed by 3587
Special Issue Editor
Interests: multiphysics system analysis and design; computational and experimental mechanics; structural health monitoring; material characterization; sensor networks; image analysis; Bayesian estimation and control; autonomous systems; cooperative robotics; inverse analysis and optimization
Special Issue Information
Dear Colleagues,
Inspection and maintenance are, by definition, tasks that require careful examination and complex contact operations and are thus human-intensive. In the completion of these tasks by an autonomous robot, the robot must be capable of configuring the details of its environment, detecting and perceiving defects to repair, planning a sequence of tasks and completing them. Since the current challenges of robotic autonomy are still limited to fundamental functions, applications to inspection and maintenance introduces various unexplored topics. For example, robotic mapping for inspection and maintenance pursues local accuracy of a known environment for completion of maintenance tasks, whereas the current mainstream for robotic mapping is directed at the global accuracy of an unknown environment for robot navigation. The maintenance task often requires higher-precision position control and more intensive force control in highly constrained environments.
This Special Issue, “Autonomous Robots for Inspection and Maintenance”, invites articles addressing problems and solutions characterized for robotic inspection and maintenance. Potential topics include, but are not limited to, the following:
- High-precision robotic mapping;
- Semantic mapping and robot cognition;
- High-precision 3D reconstruction;
- Defect detection, identification and classification;
- Complex task planning and scheduling;
- High-precision mobile manipulation in highly constrained environments;
- Intensive force control;
- Long-term autonomy;
- Human–robot collaboration;
- Learning from demonstration;
- End-effectors for inspection and/or maintenance.
Prof. Dr. Tomonari Furukawa
Guest Editor
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