Results 1 to 10 of about 142,389 (277)
Fast-RRT: A RRT-Based Optimal Path Finding Method [PDF]
Applied Sciences (Switzerland), 2021 As a sampling-based pathfinding algorithm, Rapidly Exploring Random Trees (RRT) has been widely used in motion planning problems due to the ability to find a feasible path quickly.
Wu Zhenping, Zhijun Meng, Wenlong Zhao
exaly +5 more sources
Improved RRT-Connect Algorithm Based on Triangular Inequality for Robot Path Planning
Sensors, 2021 This paper proposed a triangular inequality-based rewiring method for the rapidly exploring random tree (RRT)-Connect robot path-planning algorithm that guarantees the planning time compared to the RRT algorithm, to bring it closer to the optimum.
Jin-gu Kang, Yong-Sik Choi
exaly +4 more sources
Massively parallelizing the RRT and the RRT* [PDF]
2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2011 In recent years, the growth of the computational power available in the Central Processing Units (CPUs) of consumer computers has tapered significantly. At the same time, growth in the computational power available in the Graphics Processing Units (GPUs)
Bialkowski, Joshua John +2 more
core +5 more sources
RRT*-SMART: A Rapid Convergence Implementation of RRT* [PDF]
International Journal of Advanced Robotic Systems, 2013 Many sampling based algorithms have been introduced recently. Among them Rapidly Exploring Random Tree (RRT) is one of the quickest and the most efficient obstacle free path finding algorithm.
Jauwairia Nasir +6 more
doaj +3 more sources
Blind RRT: A probabilistically complete distributed RRT [PDF]
2013 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2013 Rapidly-Exploring Random Trees (RRTs) have been successful at finding feasible solutions for many types of problems. With motion planning becoming more computationally demanding, we turn to parallel motion planning for efficient solutions. Existing work on distributed RRTs has been limited by the overhead that global communication requires.
Cesar Rodriguez +4 more
openaire +1 more source
Integrated Motion Planning for Assembly Task with Part Manipulation Using Re-Grasping
Applied Sciences, 2020 This paper presents an integrated planner based on rapidly exploring random tree (RRT) for an assembly task with possible re-grasping. Given multiple grasp poses for the part to assemble, the planner chooses candidate grasp poses considering the ...
Ahmad Ali, Ji Yeong Lee
doaj +1 more source
Studi Performansi Algoritma Perencanaan Jalur diantara PRM, RRT, RRT* dan Informed-RRT
Telekontran : Jurnal Ilmiah Telekomunikasi, Kendali dan Elektronika Terapan, 2020 This paper will discuss a comparative performance review of several path planning algorithms. This study compares five well-known path planning algorithms, namely the Probabilistic Roadmap (PRM), Rapidly-exploring Random Tree (RRT), RRT* and Informed-RRT* algorithm. Testing is done through simulation based experiments using python.
Rumlaklak, Nelci Dessy +2 more
openaire +2 more sources
Asymptotically near-optimal RRT for fast, high-quality, motion planning [PDF]
, 2015 We present Lower Bound Tree-RRT (LBT-RRT), a single-query sampling-based algorithm that is asymptotically near-optimal. Namely, the solution extracted from LBT-RRT converges to a solution that is within an approximation factor of 1+epsilon of the optimal
Halperin, Dan, Salzman, Oren
core +1 more source
Fluid therapy and hemodynamic support in septic shock
Journal of Pediatric Critical Care, 2018 Sepsis remains one of the leading causes of mortality in children all over the world, especially in the developing nations. Early recognition of sepsis and septic shock facilitate the resuscitation, further reducing the morbidity and mortality related to
Milind Jambagi, Rakshay Shetty
doaj +1 more source
Вестник СибАДИ, 2018 The problem of planning the motion path of an unmanned vehicle is presented in the article. The results of development and the software implementation, and the research of the algorithm for constructing quasi- optimal trajectory of an unmanned vehicle ...
I. Z. Akhmetzyanov +2 more
doaj +1 more source