Geodesic
Surface Shape Identification with Legged Robots Using Tactile Sensing
Russian journal of nonlinear dynamics, Tome 20 (2024) no. 5, pp. 747-757

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This paper presents an approach to terrain shape detection using an array of tactile sensors or motor torque and encoders. A sparse point cloud at points where the surface is touched by the robot’s feet is converted into a polygonal mesh and a dense 3D point cloud using $\alpha$-shapes derived from a 2D Delaunay triangulation. Cloud-to-Cloud (C2C) and Cloud-to-Mesh (C2M) metrics are used to validate the solution. In the study, a mathematical model of the robot-surface system is developed and numerical experiments are performed on the basis of this model. A modification of Delaunay triangulation is proposed to account for impassable or unexplored areas of the surface. The results of mathematical modeling are confirmed in hardware experiments.
Keywords: tactile sensing, legged robots, identification of terrain properties, alpha shapes, mathematical modeling
Mots-clés : simulation 
@article{ND_2024_20_5_a3,
     author = {O. V. Bulichev and A. V. Maloletov},
     title = {Surface {Shape} {Identification} with {Legged} {Robots} {Using} {Tactile} {Sensing}},
     journal = {Russian journal of nonlinear dynamics},
     pages = {747--757},
     publisher = {mathdoc},
     volume = {20},
     number = {5},
     year = {2024},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/ND_2024_20_5_a3/}
}
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O. V. Bulichev; A. V. Maloletov. Surface Shape Identification with Legged Robots Using Tactile Sensing. Russian journal of nonlinear dynamics, Tome 20 (2024) no. 5, pp. 747-757. http://geodesic.mathdoc.fr/item/ND_2024_20_5_a3/