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Automated clinical production, dosimetry estimates and preclinical safety considerations for clinical translation of a SOAT1-targeted PET imaging agent. [PDF]
Nucl Med BiolKaup G +12 more
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Engineered naringenin-loaded nanoscale coordination polymers for targeted treatment of acute kidney injury. [PDF]
Mater Today BioZhou LB +11 more
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Annual trends in Mycobacterium tuberculosis detection and rifampicin resistance at a regional referral hospital in Northern Ghana, 2019-2024. [PDF]
PLoS OneWireko S +8 more
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Proceedings of the International Symposium on Combinatorial Search, 2022
Sampling-based motion planning algorithms such as Rapidly exploring Random Trees (RRTs) have been used in robotic applications for a long time. In this paper, we propose a method that combines deep learning with RRT* method. We use a neural network to learn a sample strategy for RRT*.We evaluate Deep RRT* in a collection of 2D scenarios.
Xuzhe Dang +2 more
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Sampling-based motion planning algorithms such as Rapidly exploring Random Trees (RRTs) have been used in robotic applications for a long time. In this paper, we propose a method that combines deep learning with RRT* method. We use a neural network to learn a sample strategy for RRT*.We evaluate Deep RRT* in a collection of 2D scenarios.
Xuzhe Dang +2 more
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Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006., 2006
We present a replanning algorithm for repairing rapidly-exploring random trees when changes are made to the configuration space. Instead of abandoning the current RRT, our algorithm efficiently removes just the newly-invalid parts and maintains the rest. It then grows the resulting tree until a new solution is found.
Dave Ferguson 0001 +2 more
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We present a replanning algorithm for repairing rapidly-exploring random trees when changes are made to the configuration space. Instead of abandoning the current RRT, our algorithm efficiently removes just the newly-invalid parts and maintains the rest. It then grows the resulting tree until a new solution is found.
Dave Ferguson 0001 +2 more
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SR-RRT: Selective retraction-based RRT planner
2012 IEEE International Conference on Robotics and Automation, 2012We present a novel retraction-based planner, selective retraction-based RRT, for efficiently handling a wide variety of environments that have different characteristics. We first present a bridge line-test that can identify regions around narrow passages, and then perform an optimization-based retraction operation selectively only at those regions.
Junghwan Lee +3 more
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RRT-blossom: RRT with a local flood-fill behavior
Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006., 2006This paper proposes a new variation of the RRT planner which demonstrates good performance on both loosely-constrained and highly-constrained environments. The key to the planner is an implicit flood-fill-like mechanism, a technique that is well suited to escaping local minima in highly constrained problems.
Maciej Kalisiak, Michiel van de Panne
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MK-RRT*: Multi-Robot Kinodynamic RRT Trajectory Planning
2021 International Conference on Unmanned Aircraft Systems (ICUAS), 2021This paper introduces MK-RRT*: a Multi-robot Kinodynamic RRT*-based framework for trajectory planning of multiple dynamically-modeled robots. The framework includes both tightly-coupled and loosely-coupled methods for planning. The simultaneous, tightly-coupled, method provides an asymptotically optimal solution to the multi-robot trajectory planning ...
Brennan Cain +2 more
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Proceedings of the 8th ACM SIGGRAPH Conference on Motion in Games, 2015
This paper presents a novel algorithm for real-time path-planning in a dynamic environment such as a computer game. We utilize a real-time sampling approach based on the Rapidly Exploring Random Tree (RRT) algorithm that has enjoyed wide success in robotics. More specifically, our algorithm is based on the RRT* and informed RRT* variants. We contribute
Rajamäki, Joose +3 more
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This paper presents a novel algorithm for real-time path-planning in a dynamic environment such as a computer game. We utilize a real-time sampling approach based on the Rapidly Exploring Random Tree (RRT) algorithm that has enjoyed wide success in robotics. More specifically, our algorithm is based on the RRT* and informed RRT* variants. We contribute
Rajamäki, Joose +3 more
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2015 IEEE International Conference on Robotics and Automation (ICRA), 2015
Reachable volumes are a new technique that allows one to efficiently restrict sampling to feasible/reachable regions of the planning space even for high degree of freedom and highly constrained problems. However, they have so far only been applied to graph-based sampling-based planners.
Troy McMahon +2 more
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Reachable volumes are a new technique that allows one to efficiently restrict sampling to feasible/reachable regions of the planning space even for high degree of freedom and highly constrained problems. However, they have so far only been applied to graph-based sampling-based planners.
Troy McMahon +2 more
openaire +3 more sources