This paper considers trajectory planning problems for autonomous robots in information gathering tasks. The objective of the planning is to maximize the information gathered withi...
Cindy Leung, Shoudong Huang, Ngai Ming Kwok, Gamin...
—This paper introduces a new algorithm for probabilistic motion planning in arbitrary, uncertain vector fields, with emphasis on high-level planning for Montgolfier´e balloons...
Michael T. Wolf, Lars Blackmore, Yoshiaki Kuwata, ...
Research in learning and planning in real-time strategy (RTS) games is very interesting in several industries such as military industry, robotics, and most importantly game industr...
Ibrahim Fathy, Mostafa Aref, Omar Enayet, Abdelrah...
This paper describes an approach to automatically learn planning operators by observing expert solution traces and to further refine the operators through practice in a learning-b...
— We present an approach to motion planning for highly articulated systems that aims to ensure robust execution by augmenting the planning process to reason about the robot’s a...
Philipp Michel, Christian Scheurer, James J. Kuffn...