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» Sampling-Based Motion Planning Using Predictive Models
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ICRA
2005
IEEE
134views Robotics» more  ICRA 2005»
14 years 2 months ago
Reachability Analysis of Sampling Based Planners
— The last decade, sampling based planners like the Probabilistic Roadmap Method have proved to be successful in solving complex motion planning problems. We give a reachability ...
Roland Geraerts, Mark H. Overmars
TROB
2008
134views more  TROB 2008»
13 years 9 months ago
Improving the Performance of Sampling-Based Motion Planning With Symmetry-Based Gap Reduction
Sampling-based nonholonomic and kinodynamic planning iteratively constructs solutions with sampled controls. A constructed trajectory is returned as an acceptable solution if its &...
Peng Cheng, Emilio Frazzoli, Steven M. LaValle
IROS
2006
IEEE
217views Robotics» more  IROS 2006»
14 years 3 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
ECAI
2010
Springer
13 years 9 months ago
Variable Level-Of-Detail Motion Planning in Environments with Poorly Predictable Bodies
Motion planning in dynamic environments consists of the generation of a collision-free trajectory from an initial to a goal state. When the environment contains uncertainty, preven...
Stefan Zickler, Manuela M. Veloso
AAAI
2010
13 years 10 months ago
Integrating Sample-Based Planning and Model-Based Reinforcement Learning
Recent advancements in model-based reinforcement learning have shown that the dynamics of many structured domains (e.g. DBNs) can be learned with tractable sample complexity, desp...
Thomas J. Walsh, Sergiu Goschin, Michael L. Littma...