A survey on puncture models and path planning algorithms of bevel-tipped flexible needles

Huang, Ye; Yu, Longfeng; Zhang, Feifan

doi:10.1016/j.heliyon.2024.e25002

Cited by 2 publications

(2 citation statements)

References 83 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this process, the algorithm gradually converges to an optimal solution to the problem. The formulae of the ACO algorithm ( 19) are described in [80]:…”

Section: Ant Colony Optimization (Aco)mentioning

confidence: 99%

“…In this process, the algorithm gradually converges to an optimal solution to the problem. The formulae of the ACO algorithm ( 19 ) are described in [ 80 ]:

where

is the transition probability,

represents the pheromone concentration,

is the heuristic function,

is a collection of access points, and

is a heuristic function, usually expressed as the reciprocal of the distance

between i and j .

where

represents the pheromone volatility coefficient, M is the total number of ants in the ant colony, and

represents the pheromone amount released by the k th ant.…”

Section: Heuristic Approachmentioning

confidence: 99%

See 1 more Smart Citation

Obstacle Avoidance and Path Planning Methods for Autonomous Navigation of Mobile Robot

Katona,

Neamah,

Korondi

2024

Sensors

View full text Add to dashboard Cite

Path planning creates the shortest path from the source to the destination based on sensory information obtained from the environment. Within path planning, obstacle avoidance is a crucial task in robotics, as the autonomous operation of robots needs to reach their destination without collisions. Obstacle avoidance algorithms play a key role in robotics and autonomous vehicles. These algorithms enable robots to navigate their environment efficiently, minimizing the risk of collisions and safely avoiding obstacles. This article provides an overview of key obstacle avoidance algorithms, including classic techniques such as the Bug algorithm and Dijkstra’s algorithm, and newer developments like genetic algorithms and approaches based on neural networks. It analyzes in detail the advantages, limitations, and application areas of these algorithms and highlights current research directions in obstacle avoidance robotics. This article aims to provide comprehensive insight into the current state and prospects of obstacle avoidance algorithms in robotics applications. It also mentions the use of predictive methods and deep learning strategies.

show abstract

“…In this process, the algorithm gradually converges to an optimal solution to the problem. The formulae of the ACO algorithm ( 19) are described in [80]:…”

Section: Ant Colony Optimization (Aco)mentioning

confidence: 99%

“…In this process, the algorithm gradually converges to an optimal solution to the problem. The formulae of the ACO algorithm ( 19 ) are described in [ 80 ]:

where

is the transition probability,

represents the pheromone concentration,

is the heuristic function,

is a collection of access points, and

is a heuristic function, usually expressed as the reciprocal of the distance

between i and j .

where

represents the pheromone volatility coefficient, M is the total number of ants in the ant colony, and

represents the pheromone amount released by the k th ant.…”

Section: Heuristic Approachmentioning

confidence: 99%

Obstacle Avoidance and Path Planning Methods for Autonomous Navigation of Mobile Robot

Katona,

Neamah,

Korondi

2024

Sensors

View full text Add to dashboard Cite

show abstract

Automatic Path-Planning Techniques for Minimally Invasive Stereotactic Neurosurgical Procedures—A Systematic Review

Monfaredi,

Concepcion-Gonzalez,

Acosta Julbe

et al. 2024

Sensors

View full text Add to dashboard Cite

This review systematically examines the recent research from the past decade on diverse path-planning algorithms tailored for stereotactic neurosurgery applications. Our comprehensive investigation involved a thorough search of scholarly papers from Google Scholar, PubMed, IEEE Xplore, and Scopus, utilizing stringent inclusion and exclusion criteria. The screening and selection process was meticulously conducted by a multidisciplinary team comprising three medical students, robotic experts with specialized knowledge in path-planning techniques and medical robotics, and a board-certified neurosurgeon. Each selected paper was reviewed in detail, and the findings were synthesized and reported in this review. The paper is organized around three different types of intervention tools: straight needles, steerable needles, and concentric tube robots. We provide an in-depth analysis of various path-planning algorithms applicable to both single and multi-target scenarios. Multi-target planning techniques are only discussed for straight tools as there is no published work on multi-target planning for steerable needles and concentric tube robots. Additionally, we discuss the imaging modalities employed, the critical anatomical structures considered during path planning, and the current status of research regarding its translation to clinical human studies. To the best of our knowledge and as a conclusion from this systematic review, this is the first review paper published in the last decade that reports various path-planning techniques for different types of tools for minimally invasive neurosurgical applications. Furthermore, this review outlines future trends and identifies existing technology gaps within the field. By highlighting these aspects, we aim to provide a comprehensive overview that can guide future research and development in path planning for stereotactic neurosurgery, ultimately contributing to the advancement of safer and more effective neurosurgical procedures.

show abstract

A survey on puncture models and path planning algorithms of bevel-tipped flexible needles

Cited by 2 publications

References 83 publications

Obstacle Avoidance and Path Planning Methods for Autonomous Navigation of Mobile Robot

Obstacle Avoidance and Path Planning Methods for Autonomous Navigation of Mobile Robot

Automatic Path-Planning Techniques for Minimally Invasive Stereotactic Neurosurgical Procedures—A Systematic Review

Contact Info

Product

Resources

About