Skip to Main content Skip to Navigation
Conference papers

3D Mobility Learning and Regression of Articulated, Tracked Robotic Vehicles by Physics-based Optimization

Abstract : Motion planning for robots operating on 3D rough terrain requires the synergy of various robotic capabilities, from sensing and perception to simulation, planning and prediction. In this paper, we focus on the higher level of this pipeline where by means of physics-based simulation and geometric processing we extract the information that is semantically required for an articulated, tracked robot to optimally traverse 3D terrain. We propose a model that quantifies 3D traversability by accounting for intrinsic robot characteristics and articulating capabilities together with terrain characteristics. By building upon a set of generic cost criteria for a given robot state and 3D terrain patch, we augment the traversability cost estimation by: (i) unifying pose stabilization with traversability cost estimation, (ii) introducing new parameters into the problem that have been previously overlooked and (iii) adapting geometric computations to account for the complete 3D robot body and terrain surface. We apply the proposed model on a state-of-the-art Search and Rescue robot by performing a plurality of tests under varying conditions and demonstrate its efficiency and applicability in real-time.
Complete list of metadata

Cited literature [18 references]  Display  Hide  Download

https://hal.inria.fr/hal-00769557
Contributor : Panagiotis Papadakis <>
Submitted on : Wednesday, January 2, 2013 - 11:35:36 AM
Last modification on : Wednesday, September 26, 2018 - 4:32:03 PM
Long-term archiving on: : Wednesday, April 3, 2013 - 3:47:54 AM

File

Papadakis-VRIPHYS2012.pdf
Files produced by the author(s)

Identifiers

Collections

Citation

Panagiotis Papadakis, Fiora Pirri. 3D Mobility Learning and Regression of Articulated, Tracked Robotic Vehicles by Physics-based Optimization. Virtual Reality Interaction and Physical Simulation, Eurographics, Dec 2012, Darmstadt, Germany. ⟨10.2312/PE/vriphys/vriphys12/147-156⟩. ⟨hal-00769557⟩

Share

Metrics

Record views

267

Files downloads

424