On the Dubins Traveling Salesman Problem with Neighborhoods

Váňa, Petr; Faigl, Jan

doi:10.1109/iros.2015.7353945

Cited by 24 publications

(9 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The surveillance planning algorithm will stop the adaptation if i ≤ i max or ν * are negligibly close to their respective s p , or all winner waypoint locations are inside the δ-neighborhood of the respective initial waypoint location. Local Iterative Optimization (LIO) [42] is a procedure that optimizes the whole trajectory locally, e.g., it can consecutively optimize θ i , ψ i , l i a , and l i b in the loop with waypointν i−1 , ν i , and ν i+1 . The reason (5) can optimize variables θ i , ψ i , l i a independently is tangent vector t i a and t i−1 b implicitly satisfy the smooth constraint (12).…”

Section: Stage Two: Uav Path Planning For Surveillancementioning

confidence: 99%

Occlusion-Aware UAV Path Planning for Reconnaissance and Surveillance

Zhang

Huang

2021

Drones

View full text Add to dashboard Cite

Unmanned Aerial Vehicles (UAVs) have become necessary tools for a wide range of activities including but not limited to real-time monitoring, surveillance, reconnaissance, border patrol, search and rescue, civilian, scientific and military missions, etc. Their advantage is unprecedented and irreplaceable, especially in environments dangerous to humans, for example, in radiation or pollution-exposed areas. Two path-planning algorithms for reconnaissance and surveillance are proposed in this paper, which ensures every point on the target ground area can be seen at least once in a complete surveillance circle. Moreover, the geometrically complex environments with occlusions are considered in our research. Compared with many existing methods, we decompose this problem into a waypoint-determination problem and an instance of the traveling-salesman problem.

show abstract

Section: Stage Two: Uav Path Planning For Surveillancementioning

confidence: 99%

Occlusion-Aware UAV Path Planning for Reconnaissance and Surveillance

Zhang

Huang

2021

Drones

View full text Add to dashboard Cite

show abstract

“…In ref. [103], the use of a Local Iterative Optimization strategy to independently adjust the waypoints' orientations and positions on the regions was proposed, considering that the sequence of visit is already given. Its main advantage is the low computational requirements comparing to other techniques, such as GAs.…”

Section: Non-holonomic Vehicle Routing For Visiting Regionsmentioning

confidence: 99%

“…[60] Evolutionary Decoupled Convex Ref. [103] Heuristic * Decoupled Non-convex * The DTSPN instance must respect the D 4 constraint. Fig.…”

Section: Non-holonomic Vehicle Routing For Visiting Regionsmentioning

confidence: 99%

A survey on routing problems and robotic systems

Macharet¹,

Campos²

2018

Robotica

View full text Add to dashboard Cite

SUMMARYPlanning paths that are length or time optimized or both is an age-long problem for which numerous approaches have been proposed with varied degree of success depending on the imposed constraints. Among classical instances in the literature, the Traveling Salesman Problem and the Vehicle Routing Problem have been widely studied and frequently considered in the realm of mobile robotics. Understandably, the classical formulation for such problems do not take into account many different issues that arise in real-world scenarios, such as motion constraints and dynamic environments, commonly found in actual robotic systems, and consequently the solutions have been generalized in several ways. In this work, we present a broad and comprehensive review of the classical works and recent breakthroughs regarding the routing techniques ordinarily used in robotic systems and provide references to the most fundamental works in the literature.

show abstract

“…Six algorithms for the DTSP-SCM has been compared. In particular, the proposed modifications of approaches: Alternating Algorithm (AA) [1], Local Iterative Optimization [18], Genetic algorithm [10], Memetic algorithm [11], and sampling-based approach [6] with the LKH solver [17] (denoted as the Sampling+LKH) and with the optimal Concorde solver [8], denoted as the Sampling+Concorde. Due to high computational requirements of the genetic, memetic, and sampling- based algorithms, their computational time has been limited to 1 hour.…”

Section: Performance Of Dtsp Approaches In the Dtsp-scmmentioning

confidence: 99%

The Dubins Traveling Salesman Problem With Constrained Collecting Maneuvers

Váňa

Faigl

2016

APP

Self Cite

View full text Add to dashboard Cite

In this paper, we introduce a variant of the Dubins traveling salesman problem (DTSP) that is called the Dubins traveling salesman problem with constrained collecting maneuvers (DTSP-CM). In contrast to the ordinary formulation of the DTSP, in the proposed DTSP-CM, the vehicle is requested to visit each target by specified collecting maneuver to accomplish the mission. The proposed problem formulation is motivated by scenarios with unmanned aerial vehicles where particular maneuvers are necessary for accomplishing the mission, such as object dropping or data collection with sensor sensitive to changes in vehicle heading. We consider existing methods for the DTSP and propose its modifications to use these methods to address a variant of the introduced DTSP-CM, where the collecting maneuvers are constrained to straight line segments.

show abstract

On the Dubins Traveling Salesman Problem with Neighborhoods

Cited by 24 publications

References 14 publications

Occlusion-Aware UAV Path Planning for Reconnaissance and Surveillance

Occlusion-Aware UAV Path Planning for Reconnaissance and Surveillance

A survey on routing problems and robotic systems

The Dubins Traveling Salesman Problem With Constrained Collecting Maneuvers

Contact Info

Product

Resources

About