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IJRR
2011
218views more  IJRR 2011»
12 years 10 months ago
Motion planning under uncertainty for robotic tasks with long time horizons
Abstract Partially observable Markov decision processes (POMDPs) are a principled mathematical framework for planning under uncertainty, a crucial capability for reliable operation...
Hanna Kurniawati, Yanzhu Du, David Hsu, Wee Sun Le...
IJRR
2010
162views more  IJRR 2010»
13 years 2 months ago
Planning under Uncertainty for Robotic Tasks with Mixed Observability
Partially observable Markov decision processes (POMDPs) provide a principled, general framework for robot motion planning in uncertain and dynamic environments. They have been app...
Sylvie C. W. Ong, Shao Wei Png, David Hsu, Wee Sun...
RAS
2006
111views more  RAS 2006»
13 years 3 months ago
Planning under uncertainty using model predictive control for information gathering
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...
ICRA
2010
IEEE
143views Robotics» more  ICRA 2010»
13 years 1 months ago
On the influence of ship motion prediction accuracy on motion planning and control of robotic manipulators on seaborne platforms
Robotic manipulators on non-inertial platforms, such as ships, have to endure large inertial forces due to the non-inertial motion of the platform. When the non-inertial platform&#...
Pål Johan From, Jan Tommy Gravdahl, Pieter A...
IROS
2006
IEEE
217views Robotics» more  IROS 2006»
13 years 9 months ago
Active SLAM using Model Predictive Control and Attractor based Exploration
– Active SLAM poses the challenge for an autonomous robot to plan efficient paths simultaneous to the SLAM process. The uncertainties of the robot, map and sensor measurements, a...
Cindy Leung, Shoudong Huang, Gamini Dissanayake