Optimal grid-free path planning across arbitrarily contoured terrain with anisotropic friction and gravity effects

Rowe, Neil C.; Ross, R.S.

doi:10.1109/70.62043

Cited by 61 publications

(74 citation statements)

References 13 publications

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“…The minimum-time trajectories of motion are calculated using the elevation changes between adjacent isolines. Later in [13], Rowe and Ross introduced an energy-cost model for mobile robots navigating in uneven terrains. In their model, cost of the traversal between two points is defined as the energy loss due to friction and gravity.…”

Section: A Related Workmentioning

confidence: 99%

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Finding energy-efficient paths on uneven terrains

Ganganath

Cheng

Tse

2014

2014 10th France-Japan/ 8th Europe-Asia Congress on Mecatronics (MECATRONICS2014- Tokyo)

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Abstract-Mobile robots are increasingly getting popular in outdoor applications. Long period of continuous operations are common in such applications. Therefore, robot motions need to be optimized to minimize their energy consumption. Shortest paths do not always guarantee minimum energy consumptions of mobile robots. This paper proposes a novel algorithm to generate energyefficient paths on uneven terrains using an established energycost model for mobile robots. Terrains are represented using grid based elevation maps. Similar to A* algorithm, the energy-cost of traversing through a particular gird depends on a heuristic energy-cost estimation from the current location to the goal. The proposed heuristic energy-cost function makes it possible to generate zigzag-like path patterns on steep hills under the power limitations of the robot. Therefore, the proposed method can find physically feasible energy-efficient paths on any given terrain, provided that such paths exist. Simulation results presented in this paper demonstrate the performance of the proposed algorithm on uneven terrains maps.

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Section: A Related Workmentioning

confidence: 99%

“…In this work, we use the energy-cost model developed by Rowe and Ross [13]. Let n c be the current location (grid) of the robot in a given grid map, and n n be a neighboring grid which the robot will move to in next time step.…”

Section: B Energy-cost Modelmentioning

confidence: 99%

Finding energy-efficient paths on uneven terrains

Ganganath

Cheng

Tse

2014

2014 10th France-Japan/ 8th Europe-Asia Congress on Mecatronics (MECATRONICS2014- Tokyo)

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“…In each of these areas, researchers create the models specific to said application; unfortunately their analysis and results cannot be easily transferred to other problems. For example, the problem of computing an optimal path for a mobile robot considers friction and gravity forces for various regions of terrain, and then uses this direction and location dependent cost function to find a path that minimizes the total energy consumption of the robot [34,62,63,68]. Since surface contour does not change over time, this set of problems only considers path finding in a static environment.…”

Section: Literature Overviewmentioning

confidence: 99%

“…Furthermore, presence of obstacles is not commonly addressed in the published studies. For example, Rowe [62] and Rowe and Ross [63] study optimal path finding for a mobile agent (e.g., robot or vehicle) across hilly terrains, where a simple and specific physical model of friction and gravity forces is used to compute the anisotropic cost function for the agent.…”

Section: Related Workmentioning

confidence: 99%

“…However in practice, the speed function V (θ) can take on the value of zero for some headings, i.e., leading to a 'stall'. For example, a vehicle traveling across some hilly terrain might encounter impermissible headings due to overturn danger or power limitations [63]. On another hand, a sailing boat can not travel in head sea corresponding to a zero speed for that heading [57].…”

Section: Problem Feasibility and Fastest-path Finding For A Non-negatmentioning

confidence: 99%

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Optimal path finding in direction, location, and time dependent environments

Dolinskaya

2012

Naval Research Logistics

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This article examines optimal path finding problems where cost function and constraints are direction, location, and time dependent. Recent advancements in sensor and data‐processing technology facilitate the collection of detailed real‐time information about the environment surrounding a ground vehicle, an airplane, or a naval vessel. We present a navigation model that makes use of such information. We relax a number of assumptions from existing literature on path‐finding problems and create an accurate, yet tractable, model suitable for implementation for a large class of problems. We present a dynamic programming model which integrates our earlier results for direction‐dependent, time and space homogeneous environment, and consequently, improves its accuracy, efficiency, and run‐time. The proposed path finding model also addresses limited information about the surrounding environment, control‐feasibility of the considered paths, such as sharpest feasible turns a vehicle can make, and computational demands of a time‐dependent environment. To demonstrate the applicability and performance of our path‐finding algorithm, computational experiments for a short‐range ship routing in dynamic wave‐field problem are presented. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012

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Driving on Point Clouds: Motion Planning, Trajectory Optimization, and Terrain Assessment in Generic Nonplanar Environments

Krüsi

Furgale

Bosse

et al. 2016

Journal of Field Robotics

132

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We present a practical approach to global motion planning and terrain assessment for ground robots in generic three-dimensional (3D) environments, including rough outdoor terrain, multilevel facilities, and more complex geometries. Our method computes optimized six-dimensional trajectories compliant with curvature and continuity constraints directly on unordered point cloud maps, omitting any kind of explicit surface reconstruction, discretization, or topology extraction. We assess terrain geometry and traversability on demand during motion planning, by fitting robot-sized planar patches to the map and analyzing the local distribution of map points. Our motion planning approach consists of sampling-based initial trajectory generation, followed by precise local optimization according to a custom cost measure, using a novel, constraint-aware trajectory optimization paradigm. We embed these methods in a complete autonomous navigation system based on localization and mapping by means of a 3D laser scanner and iterative closest point matching, suitable for both static and dynamic environments. The performance of the planning and terrain assessment algorithms is evaluated in offline experiments using recorded and simulated sensor data. Finally, we present the results of navigation experiments in three different environments-rough outdoor terrain, a two-level parking garage, and a dynamic environment, demonstrating how the proposed methods enable autonomous navigation in complex 3D terrain. C

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Optimal grid-free path planning across arbitrarily contoured terrain with anisotropic friction and gravity effects

Abstract: Anisotropic (heading-dependent) phenomena arise in the "two-and-one-half-dimensional" path-planning

Cited by 61 publications

References 13 publications

Finding energy-efficient paths on uneven terrains

Finding energy-efficient paths on uneven terrains

Optimal path finding in direction, location, and time dependent environments

Driving on Point Clouds: Motion Planning, Trajectory Optimization, and Terrain Assessment in Generic Nonplanar Environments

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