Effect of Planning Period on MPC-based Navigation for a Biped Robot in a Crowd
| العنوان: | Effect of Planning Period on MPC-based Navigation for a Biped Robot in a Crowd |
|---|---|
| المؤلفون: | Thierry Fraichard, Matteo Ciocca, Pierre-Brice Wieber |
| المساهمون: | Interaction située avec les objets et environnements intelligents (PERVASIVE), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire d'Informatique de Grenoble (LIG ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Institut National de Recherche en Informatique et en Automatique (Inria), ANR-11-LABX-0025,PERSYVAL-lab,Systemes et Algorithmes Pervasifs au confluent des mondes physique et numérique(2011) |
| المصدر: | IROS 2019-IEEE/RSJ International Conference on Intelligent Robots and Systems IROS 2019-IEEE/RSJ International Conference on Intelligent Robots and Systems, Nov 2019, Macau, China. pp.1-8, ⟨10.1109/IROS40897.2019.8968070⟩ IROS |
| بيانات النشر: | HAL CCSD, 2019. |
| سنة النشر: | 2019 |
| مصطلحات موضوعية: | 0209 industrial biotechnology, Computer science, business.industry, 02 engineering and technology, Motion (physics), Model predictive control, 020901 industrial engineering & automation, Position (vector), 11. Sustainability, 0202 electrical engineering, electronic engineering, information engineering, Robot, [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO], 020201 artificial intelligence & image processing, Computer vision, Artificial intelligence, business, Collision avoidance, ComputingMilieux_MISCELLANEOUS, Biped robot |
| الوصف: | We control a biped robot moving in a crowd with a Model Predictive Control (MPC) scheme that generates stable walking motions, with automatic footstep placement. Most walking strategies propose to re-plan the walking motion to adapt to changing environments only once at every footstep. This is because a footstep is planted on the ground, it usually stays there at a constant position until the next footstep is initiated, what naturally constrains the capacity for the robot to react and adapt its motion in between footsteps. The objective of this paper is to measure if re-planning the walking motion more often than once at every footstep can lead to an improvement in collision avoidance when navigating in a crowd. Our result is that re-planning twice (or more) during each footstep leads to a significant reduction of the number of collisions when walking in a crowd, but depends on the density of the crowd. |
| اللغة: | English |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5bf241acc97b68508966d8be074e7aeb https://hal.inria.fr/hal-02267426 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....5bf241acc97b68508966d8be074e7aeb |
| قاعدة البيانات: | OpenAIRE |
| الوصف غير متاح. |