6,904 research outputs found
Hierarchical D ∗ algorithm with materialization of costs for robot path planning
In this paper a new hierarchical extension of the D
∗ algorithm for robot path planning is introduced. The hierarchical D
∗
algorithm uses a down-top strategy and a set of precalculated paths (materialization of path costs) in order to improve performance.
This on-line path planning algorithm allows optimality and specially lower computational time. H-Graphs (hierarchical graphs)
are modified and adapted to support on-line path planning with materialization of costs and multiple hierarchical levels. Traditional
on-line robot path planning focused in horizontal spaces is also extended to vertical and interbuilding spaces. Some experimental
results are showed and compared to other path planning algorithms
An Approach to Improve Multi objective Path Planning for Mobile Robot Navigation using the Novel Quadrant Selection Method
Currently, automated and semi-automated industries need multiple objective path planning algorithms for mobile robot applications. The multi-objective optimisation algorithm takes more computational effort to provide optimal solutions. The proposed grid-based multi-objective global path planning algorithm [Quadrant selection algorithm (QSA)] plans the path by considering the direction of movements from starting position to the target position with minimum computational effort. Primarily, in this algorithm, the direction of movements is classified into quadrants. Based on the selection of the quadrant, the optimal paths are identified. In obstacle avoidance, the generated feasible paths are evaluated by the cumulative path distance travelled, and the cumulative angle turned to attain an optimal path. Finally, to ease the robot’s navigation, the obtained optimal path is further smoothed to avoid sharp turns and reduce the distance. The proposed QSA in total reduces the unnecessary search for paths in other quadrants. The developed algorithm is tested in different environments and compared with the existing algorithms based on the number of cells examined to obtain the optimal path. Unlike other algorithms, the proposed QSA provides an optimal path by dramatically reducing the number of cells examined. The experimental verification of the proposed QSA shows that the solution is practically implementable
Hierarchical Path Search with Partial Materialization of Costs for a Smart Wheelchair
In this paper, the off-line path planner module of a smart wheelchair aided navigation
system is described. Environmental information is structured into a hierarchical graph (H-graph) and
used either by the user interface or the path planner module. This information structure facilitates
efficient path search and easier information access and retrieval. Special path planning issues like
planning between floors of a building (vertical path planning) are also viewed. The H-graph proposed
is modelled by a tree. The hierarchy of abstractions contained in the tree has several levels of detail.
Each abstraction level is a graph whose nodes can represent other graphs in a deeper level of the
hierarchy. Path planning is performed using a path skeleton which is built from the deepest
abstraction levels of the hierarchy to the most upper levels and completed in the last step of the
algorithm. In order not to lose accuracy in the path skeleton generation and speed up the search, a set
of optimal subpaths are previously stored in some nodes of the H-graph (path costs are partially
materialized). Finally, some experimental results are showed and compared to traditional heuristic
search algorithms used in robot path planning.Comisión Interministerial de Ciencia y Tecnología TER96-2056-C02-0
Recommended from our members
Mobile robotics in agricultural operations: A narrative review on planning aspects
The advent of mobile robots in agriculture has signaled a digital transformation with new automation technologies optimize a range of labor-intensive, resources-demanding, and time-consuming agri-field operations. To that end a generally accepted technical lexicon for mobile robots is lacking as pertinent terms are often used interchangeably. This creates confusion among research and practice stakeholders. In addition, a consistent definition of planning attributes in automated agricultural operations is still missing as relevant research is sparse. In this regard, a “narrative” review was adopted (1) to provide the basic terminology over technical aspects of mobile robots used in autonomous operations and (2) assess fundamental planning aspects of mobile robots in agricultural environments. Based on the synthesized evidence from extant studies, seven planning attributes have been included: (i) high-level control-specific attributes, which include reasoning architecture, the world model, and planning level, (ii) operation-specific attributes, which include locomotion–task connection and capacity constraints, and (iii) physical robot-specific attributes, which include vehicle configuration and vehicle kinematics.</jats:p
Computational intelligence approaches to robotics, automation, and control [Volume guest editors]
No abstract available
- …