Zobrazeno 1 - 10
of 38
pro vyhledávání: '"Majid Khadiv"'
Publikováno v:
IEEE Access, Vol 12, Pp 36874-36881 (2024)
Robotic exoskeletons provide a viable means for enabling individuals with limited or no walking ability to traverse various surfaces with maximal external support to the patient’s body. However, to achieve effective performance, it is crucial to co
Externí odkaz:
https://doaj.org/article/5e29344a3ec84e5a8b636011ade933f0
Publikováno v:
Frontiers in Robotics and AI, Vol 9 (2022)
We present a general, two-stage reinforcement learning approach to create robust policies that can be deployed on real robots without any additional training using a single demonstration generated by trajectory optimization. The demonstration is used
Externí odkaz:
https://doaj.org/article/d4c0c5fffe5a4282a4f2666cd3e80165
Publikováno v:
Applied Sciences, Vol 11, Iss 1, p 353 (2020)
Contacts between robots and environment are often assumed to be rigid for control purposes. This assumption can lead to poor performance when contacts are soft and/or underdamped. However, the problem of balancing on soft contacts has not received mu
Externí odkaz:
https://doaj.org/article/8dc820107bfc453ea5fef9f22c10c7bf
Autor:
Ahmadreza Shahrokhshahi, Majid Khadiv, Ali Taherifar, Saeed Mansouri, Edward J. Park, Siamak Arzanpour
Publikováno v:
IEEE Robotics and Automation Letters. 7:9020-9027
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a054a3ab098766ee04770364c541cb35
https://doi.org/10.1109/lra.2022.3187262
https://doi.org/10.1109/lra.2022.3187262
Autor:
Avadesh Meduri, Paarth Shah, Julian Viereck, Majid Khadiv, Ioannis Havoutis, Ludovic Righetti
Publikováno v:
IEEE Transactions on Robotics (Submitted)
Online planning of whole-body motions for legged robots is challenging due to the inherent nonlinearity in the robot dynamics. In this work, we propose a nonlinear model predictive control (MPC) framework, the BiConMP which can generate whole body tr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9f9a1c354568f57aad9086c19cef4770
Publikováno v:
Applied Sciences, Vol 11, Iss 353, p 353 (2021)
Applied Sciences
Volume 11
Issue 1
Applied Sciences
Volume 11
Issue 1
Contacts between robots and environment are often assumed to be rigid for control purposes. This assumption can lead to poor performance when contacts are soft and/or underdamped. However, the problem of balancing on soft contacts has not received mu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::871d85822382ecd0b9d6427b99c1060f
https://www.mdpi.com/2076-3417/11/1/353
https://www.mdpi.com/2076-3417/11/1/353
Autor:
Ahmadreza Shahrokhshahi, Saeed Mansouri, Seyed Saeid Mohtasebi, Aghil Yousefi-Koma, Majid Khadiv
Publikováno v:
Journal of Intelligent & Robotic Systems. 94:43-59
This study addresses optimal walking pattern generation for SURENA III humanoid robot in a stair-climbing scenario. To this end, the kinematic configuration of the 31-DOF humanoid robot is studied. Integrating the detailed dynamic properties of the r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::63bb4305dce3fa71a723fb6d735156d6
https://doi.org/10.1007/s10846-018-0959-5
https://doi.org/10.1007/s10846-018-0959-5
Publikováno v:
IEEE Robotics and Automation Letters
In this paper, we present a novel two-level variable Horizon Model Predictive Control (VH-MPC) framework for bipedal locomotion. In this framework, the higher level computes the landing location and timing (horizon length) of the swing foot to stabil
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2250c3439dac42cc0d5272389158cd92
Autor:
Mohammad Hasan Yeganegi, Majid Khadiv, Andrea Del Prete, S. Ali A. Moosavian, Ludovic Righetti
Publikováno v:
IEEE Transactions on Robotics
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=r3c4b2081b22::7f6aa1503641e9e0c61df0cba3bad236
Publikováno v:
ICRA
2021 IEEE-RAS International Conference on Robotics and Automation (ICRA)
2021 IEEE International Conference on Robotics and Automation (ICRA)
2021 IEEE-RAS International Conference on Robotics and Automation (ICRA)
2021 IEEE International Conference on Robotics and Automation (ICRA)
Reactive stepping and push recovery for biped robots is often restricted to flat terrains because of the difficulty in computing capture regions for nonlinear dynamic models. In this paper, we address this limitation by using reinforcement learning t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9d884837ea24ec8d5470388db22de82a
http://arxiv.org/abs/2010.14834
http://arxiv.org/abs/2010.14834