Journal ArticleDOI
Hierarchical path planning of mobile robots in complex indoor environments
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TLDR
The FHD* algorithm guarantees the optimality of the global path, and requires considerably less time for the path replanning operations, and can be easily extended to the problem of path planning between different floors or buildings.Abstract:
Inspired by the Hierarchical D* (HD*) algorithm of D. Cagigas (Cagigas, 2005), in this paper we introduce a novel hierarchical path planning algorithm called Focussed Hierarchical D* (FHD*). Unlike the original HD* algorithm, the FHD* algorithm guarantees the optimality of the global path, and requires considerably less time for the path replanning operations. This is achieved by several modifications: (i) optimal placement of the so-called bridge nodes needed for hierarchy creation, (ii) focusing the search around the optimal path, which reduces the search area without loss of optimality, and (iii) introduction of partial starts and partial goals, which further reduce computational time of replanning operations. The FHD* algorithm was tested in a multiroom indoor environment and compared to the original HD* algorithm, non-hierarchical D* algorithm, and Focussed D* algorithm under the same conditions. The FHD* algorithm significantly outperforms other algorithms with respect to the computational time. Furthermore, it can be easily extended to the problem of path planning between different floors or buildings.read more
Citations
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Journal ArticleDOI
Two-way D* algorithm for path planning and replanning
Marija Dakulovic,Ivan Petrović +1 more
TL;DR: This work introduces a novel path planning and replanning algorithm - the two-way D^* (TWD^*) algorithm - based on a two-dimensional occupancy grid map of the environment that can find optimal paths in weighted occupancy grid maps.
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Knowledge representation and management in indoor mobile environments
TL;DR: A data and knowledge representation of an indoor environment that takes into account user-centred contextual dimensions and mobile data management issues is developed, and a hierarchical, context-dependent, and feature-based indoor spatial data model is introduced.
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Obstacle Avoiding Robot
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Two-dimensional laser-based environment exploration and recognition for service robots
TL;DR: A new geometric model of the environment that is constructed with line segments and ellipses by estimating geometric properties and extracting geometric discontinuities is presented, which can effectively explore and recognize a large-scale indoor environment in real time.
Journal ArticleDOI
Hierarchical Path-Planning for Mobile Robots Using a Skeletonization-Informed Rapidly Exploring Random Tree*
TL;DR: An efficient, hierarchical, two-dimensional path-planning method for large complex environments is presented and the entire path from the start position to the goal position can be achieved more quickly and more robustly using the hierarchical approach than the conventional single-layered method.
References
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TL;DR: This paper reformulated the manipulator con trol problem as direct control of manipulator motion in operational space—the space in which the task is originally described—rather than as control of the task's corresponding joint space motion obtained only after geometric and geometric transformation.
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Robot Motion Planning
TL;DR: This chapter discusses the configuration space of a Rigid Object, the challenges of dealing with uncertainty, and potential field methods for solving these problems.
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Real-time obstacle avoidance for manipulators and mobile robots
TL;DR: This paper reformulated the manipulator control problem as direct control of manipulator motion in operational space-the space in which the task is originally described-rather than as control of the task's corresponding joint space motion obtained only after geometric and kinematic transformation.
Journal ArticleDOI
The dynamic window approach to collision avoidance
TL;DR: This approach, designed for mobile robots equipped with synchro-drives, is derived directly from the motion dynamics of the robot and safely controlled the mobile robot RHINO in populated and dynamic environments.
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Problem-Solving Methods in Artificial Intelligence
TL;DR: This paper will concern you to try reading problem solving methods in artificial intelligence as one of the reading material to finish quickly.