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
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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/

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