A hybrid inductive learning-based and deductive reasoning-based 3-D path planning method in complex environments

Traditional path planning methods, such as sampling-based and iterative approaches, allow for optimal path’s computation in complex environments. Nonetheless, environment exploration is subject to rules which can be obtained by domain experts and could be used for improving the search. The present w...

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Vydáno v:Autonomous robots Ročník 46; číslo 5; s. 645 - 666
Hlavní autoři: Segato, Alice, Calimeri, Francesco, Testa, Irene, Corbetta, Valentina, Riva, Marco, De Momi, Elena
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.06.2022
Springer Nature B.V
Témata:
Algorithms
Artificial Intelligence
Automation
Barriers
Brain research
Computer Imaging
Computing time
Control
Domains
Engineering
Explicit knowledge
Iterative methods
Kinematics
Learning
Logic programming
Mechatronics
Methods
Path planning
Pattern Recognition and Graphics
Planning
Robotics
Robotics and Automation
Robots
Smoothness
Subject specialists
Vision
Path planning
Surgical robotics
Artificial intelligence
Answer set programming
Machine learning
Steerable needles
ISSN:0929-5593, 1573-7527
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Popis
Shrnutí:Traditional path planning methods, such as sampling-based and iterative approaches, allow for optimal path’s computation in complex environments. Nonetheless, environment exploration is subject to rules which can be obtained by domain experts and could be used for improving the search. The present work aims at integrating inductive techniques that generate path candidates with deductive techniques that choose the preferred ones. In particular, an inductive learning model is trained with expert demonstrations and with rules translated into a reward function, while logic programming is used to choose the starting point according to some domain expert’s suggestions. We discuss, as use case, 3-D path planning for neurosurgical steerable needles. Results show that the proposed method computes optimal paths in terms of obstacle clearance and kinematic constraints compliance, and is able to outperform state-of-the-art approaches in terms of safety distance-from-obstacles respect, smoothness, and computational time.
Bibliografie:ObjectType-Article-1
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ISSN:0929-5593
1573-7527
DOI:10.1007/s10514-022-10042-z