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Accelerating Partial-Order Planners: Some Techniques for Effective Search Control and Pruning [article]

A. Gerevini, L. Schubert
1996 arXiv   pre-print
We propose some domain-independent techniques for bringing well-founded partial-order planners closer to practicality.  ...  The pruning technique based on parameter domains often gave speedups by an order of magnitude or more for difficult problems, both with the default UCPOP search strategy and with our improved strategy.  ...  Acknowledgements This work amalgamates and extends two conference papers on improving search and using computed parameter domains (Gerevini & Schubert, 1996) to accelerate partial-order planners.  ... 
arXiv:cs/9609101v1 fatcat:hmcvbqbcgjcvln6vvkvmrdu7ey

Accelerating Partial-Order Planners: Some Techniques for Effective Search Control and Pruning

A. Gerevini, L. Schubert
1996 The Journal of Artificial Intelligence Research  
We propose some domain-independent techniques for bringing well-founded partial-order planners closer to practicality.  ...  The pruning technique based on parameter domains often gave speedups by an order of magnitude or more for difficult problems, both with the default UCPOP search strategy and with our improved strategy.  ...  Acknowledgements This work amalgamates and extends two conference papers on improving search using computed parameter domains Gerevini & Schubert, 1996 to accelerate partial-order planners.  ... 
doi:10.1613/jair.316 fatcat:ojce4ywqhzfktew3tsvczv7pne

A sampling-based strategy planner for nondeterministic hybrid systems

Morteza Lahijanian, Lydia E. Kavraki, Moshe Y. Vardi
2014 2014 IEEE International Conference on Robotics and Automation (ICRA)  
During the exploration phase, a search tree is grown in the hybrid state space by sampling state and control spaces for a fixed amount of time.  ...  The planner uses sampling-based techniques and gametheoretic approaches to generate a series of plans and decision choices that increase the chances of success within a fixed time budget.  ...  The authors would like to thank Ryan Luna from Rice University for his valuable input and great deal of assistance with the implementation of the algorithms.  ... 
doi:10.1109/icra.2014.6907292 dblp:conf/icra/LahijanianKV14 fatcat:ull6qnrbxvexpbefffdn6i7u6q

TuPAQ: An Efficient Planner for Large-scale Predictive Analytic Queries [article]

Evan R. Sparks, Ameet Talwalkar, Michael J. Franklin, Michael I. Jordan, Tim Kraska
2015 arXiv   pre-print
In this work, we build upon these recent efforts and propose an integrated PAQ planning architecture that combines advanced model search techniques, bandit resource allocation via runtime algorithm introspection  ...  Recent efforts aiming to automate this process have focused on single node implementations and have assumed that model training itself is a black box, thus limiting the effectiveness of such approaches  ...  , Peter Bailis, Alan Fekete, Dan Crankshaw, Sanjay Krishnan, Xinghao Pan, and Kevin Jamieson for helpful feedback.  ... 
arXiv:1502.00068v2 fatcat:l5ane47jazgq7cm3w7wh5cmho4

Accelerating partial order planners by improving plan and goal choices

L. Schubert, A. Gerevini
Proceedings of 7th IEEE International Conference on Tools with Artificial Intelligence  
We describe some simple domain-independent improvements to planre nement strategies for well-founded partial order planning that promise to bring this style of planning closer to practicality.  ...  second-highest priority to goals that can only be achieved uniquely, and otherwise uses LIFO prioritization.  ...  for well-founded nonlinear planning, TWEAK 6] (Chapman's partial-order planner based on his \modal truth criterion") and SNLP 23] (another systematic partial-order planner using propositional STRIPS  ... 
doi:10.1109/tai.1995.479839 dblp:conf/ictai/SchubertG95 fatcat:yaxuv7ohpnfr5knldpjlekfv7i

Integrating a Path Planner and an Adaptive Motion Controller for Navigation in Dynamic Environments

Junjie Zeng, Long Qin, Yue Hu, Quanjun Yin, Cong Hu
2019 Applied Sciences  
These improvements make the IA3C controller converge faster and become more adaptive to incomplete, noisy information caused by partial observability.  ...  Actor-Critic) in this paper for robot navigation in dynamic environments through continuous controlling signals.  ...  path planner, and the second for the robust local motion controller.  ... 
doi:10.3390/app9071384 fatcat:cqjgcfly6bfnthu7zwxymm6p2i

Contingent planning under uncertainty via stochastic satisfiability

Stephen M. Majercik, Michael L. Littman
2003 Artificial Intelligence  
Our planner, ZANDER, can solve arbitrary, goal-oriented, finite-horizon partially observable Markov decision processes (POMDPs).  ...  We describe a new planning technique that efficiently solves probabilistic propositional contingent planning problems by converting them into instances of stochastic satisfiability (SSAT) and solving these  ...  Acknowledgements We would like to thank Blai Bonet, Zhengzhu Feng, Eric Hansen, Henry Kautz, Donald Loveland, Nilufer Onder, Mark Peot, Toni Pitassi, and our anonymous reviewers for their help during this  ... 
doi:10.1016/s0004-3702(02)00379-x fatcat:qio3lcif6zg4fkzo3kjkwpzh5a

High-dimensional underactuated motion planning via task space control

A. Shkolnik, R. Tedrake
2008 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems  
., walking robots), and necessitates planning for long-term control solutions.  ...  Here we present a model-based dimensionality reduction technique based on an extension of partial feedback linearization control into a task-space framework.  ...  INTRODUCTION A robotic system is "underactuated" if a control system cannot produce arbitrary accelerations in some of the degrees of freedom at every instant in time.  ... 
doi:10.1109/iros.2008.4651150 dblp:conf/iros/ShkolnikT08 fatcat:zejjpq5pcngwvnw4rt54e3ciqe

Autonomous miniature blimp navigation with online motion planning and re-planning

J. Muller, N. Kohler, W. Burgard
2011 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems  
These aspects, paired with their high-dimensional state space, demand efficient planning and control techniques.  ...  Based on this, our approach can quickly provide a partial trajectory, which is extended and refined in the consecutive planning steps.  ...  Obstacles are shown in black. re-use by searching for the node that will be reached at t max and pruning (line 1 to 3) similar to Bekris and Kavraki [1] .  ... 
doi:10.1109/iros.2011.6094632 dblp:conf/iros/MullerKB11 fatcat:tuz2v5f33bhs3hen3lmx34buua

Autonomous miniature blimp navigation with online motion planning and re-planning

Jorg Muller, Norman Kohler, Wolfram Burgard
2011 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems  
These aspects, paired with their high-dimensional state space, demand efficient planning and control techniques.  ...  Based on this, our approach can quickly provide a partial trajectory, which is extended and refined in the consecutive planning steps.  ...  Obstacles are shown in black. re-use by searching for the node that will be reached at t max and pruning (line 1 to 3) similar to Bekris and Kavraki [1] .  ... 
doi:10.1109/iros.2011.6048315 fatcat:5pvtvwoejzaepcvtm7tfqntdcu

E^3MoP: Efficient Motion Planning Based on Heuristic-Guided Motion Primitives Pruning and Path Optimization With Sparse-Banded Structure [article]

Jian Wen, Xuebo Zhang, Haiming Gao, Jing Yuan, Yongchun Fang
2021 arXiv   pre-print
path planner to further improve the computational efficiency of graph search, and 2) a new soft-constrained local path optimization approach is proposed, wherein the sparse-banded system structure of  ...  Compared with existing approaches, the novelty of this work is twofold: 1) a novel heuristic-guided pruning strategy of motion primitives is proposed and fully integrated into the state lattice-based global  ...  ACKNOWLEDGMENT The data for the Intel Research Lab is available from the Radish data set repository [49] . The authors gratefully thank Dirk Hähnel for providing this data set.  ... 
arXiv:2012.08892v3 fatcat:m2ny7rf4jrcelmfcrp2bqahgna

Planning for Gene Regulatory Network Intervention

Daniel Bryce, Seungchan Kim
2006 2006 IEEE/NLM Life Science Systems and Applications Workshop  
While some techniques exist for reasoning with cellular processes, few take advantage of the flexible and scalable algorithms popularized in AI research.  ...  In this domain, where scalability is crucial for feasible application, we apply AI planning based search techniques and demonstrate their advantage over existing enumerative methods.  ...  We thank Ashish Choudhary, Edward Dougherty, William Cushing, and Subbarao Kambhampati for helpful discussions.  ... 
doi:10.1109/lssa.2006.250382 fatcat:wcmk356vxvfqzen3murxzzzclu

Randomised MPC-based motion-planning for mobile robot obstacle avoidance

A. Brooks, T. Kaupp, A. Makarenko
2009 2009 IEEE International Conference on Robotics and Automation  
The algorithm is improved by seeding the tree using the best control trajectory from the previous iteration, and by pruning branches based on a bound to the cost function and the best trajectory found  ...  The algorithm has been used to drive autonomously for a combined total on the order of hundreds of hours.  ...  The effects are analysed in Figure 5 . For a given number of expansions, pruning results in a non-trivial improvement in plan quality and an approximate halving of the time required for planning.  ... 
doi:10.1109/robot.2009.5152240 dblp:conf/icra/BrooksKM09 fatcat:gky4rfk44rdzfgeqazrjejdody

Taming Numbers and Durations in the Model Checking Integrated Planning System

S. Edelkamp
2003 The Journal of Artificial Intelligence Research  
The linear time algorithm to compute the parallel plan bypasses known NP hardness results for partial ordering by scheduling plans with respect to the set of actions and the imposed precedence relations  ...  The Model Checking Integrated Planning System (MIPS) is a temporal least commitment heuristic search planner based on a flexible object-oriented workbench architecture.  ...  Acknowledgments The author would like to thank Derek Long and Maria Fox for helpful discussions concerning this paper and Malte Helmert for his cooperation in the second planning competition.  ... 
doi:10.1613/jair.1302 fatcat:h3uxy2ithfb4fhqlcyeup4p2vu

Hybrid Risk-Aware Conditional Planning with Applications in Autonomous Vehicles

Xin Huang, Ashkan Jasour, Matthew Deyo, Andreas Hofmann, Brian C. Williams
2018 2018 IEEE Conference on Decision and Control (CDC)  
Off-line computations include generating a library of probabilistic maneuvers for the controllable agent and planning an initial motion policy to execute.  ...  The problem is modeled as a chance-constrained Partially Observable Markov Decision Process (CC-POMDP) with one controllable agent and multiple uncontrollable agents, each of which can choose from a set  ...  Pruning the search space using risk is domain dependent and less effective in safer planning scenarios.  ... 
doi:10.1109/cdc.2018.8619771 dblp:conf/cdc/HuangJDHW18 fatcat:t76i3erebrdspf5tnfdwmwawpy
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