Optimal Robot Motion Planning
A special issue of Robotics (ISSN 2218-6581).
Deadline for manuscript submissions: closed (31 May 2021) | Viewed by 4875
Special Issue Editors
Interests: robot mission planning; robot control; design and mechatronics; modelling of electromechanical systems
Interests: mechatronics design; gripper design; robot kinematics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear colleague,
Τhis Special Issue presents an important topic in robotics, focusing on optimal robot motion planning of mobile robots and manipulators as well as its applications such as on autonomous driving and on marine vehicles.
Today, robots are requested to operate in real-world problems in complicated, dynamic, unstructured, and open environments and their motion planning becomes more challenging. A manipulator or a mobile robot needs to avoid obstacles and move along the appropriate path for each task in an optimal way. However, to deploy novel robotic applications in practice, the traditional approach to robotic development does not suffice. Thus, there is an increasing need for advanced algorithmic tools enabling powerful capabilities for the robots. In most applications, the key challenge is to plan the optimal motion that still guarantees constraint satisfaction. Optimal robot motion planning is not a brand new topic but there is a recent renewed interest and a growing variety of methods for motion planning, which vary in terms of their optimality properties.
This Special Issue fits within the scope of Robotics and aims to present and discuss major research challenges, latest developments, and recent advances in optimal motion planning for robots (such as unmanned underwater or surface vehicles, unmanned ground and aerial vehicles, autonomous vehicles, manipulators, etc.) which are requested to operate in a real world environment.
Prof. Dr. Nikolaos Aspragathos
Assist. Prof. Dr. Vassilis C. Moulianitis
Assist. Prof. Dr. Elias K. Xidias
Guest Editors
Manuscript Submission Information
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Keywords
- robot motion planning
- unmanned vehicles
- industrial robots
- microparts motion planning
- evolutionary algorithms
- machine learning methods
- reinforcement learning
- computational geometry
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