2016
DOI: 10.1007/978-3-319-32552-1_48
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Modeling and Control of Legged Robots

Abstract: HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des labor… Show more

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Cited by 147 publications
(172 citation statements)
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“…In practice, we evaluated the integral of the norm of the joint torques (during one locomotion cycle) and we compared it with the norm of the joint torques related to inertial forces. For the range of walking speed of our locomotion experiments, [5,10,15,15] cm/s, we found that the inertial forces accounted only for [9.5,11.5,15, 22]% of the total joint torques. Therefore, since the influence of the trunk inertia tensor is minor, its identification is out of the scope of this work.…”
Section: Online Trunk Com Identificationmentioning
confidence: 80%
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“…In practice, we evaluated the integral of the norm of the joint torques (during one locomotion cycle) and we compared it with the norm of the joint torques related to inertial forces. For the range of walking speed of our locomotion experiments, [5,10,15,15] cm/s, we found that the inertial forces accounted only for [9.5,11.5,15, 22]% of the total joint torques. Therefore, since the influence of the trunk inertia tensor is minor, its identification is out of the scope of this work.…”
Section: Online Trunk Com Identificationmentioning
confidence: 80%
“…In addition, most stability criteria in legged locomotion are heavily affected by model errors as they depend on the estimation of the robot CoM [10]. A common strategy to increase robustness against CoM uncertainties [11] is to ensure a reasonable stability margin inside the support polygon.…”
Section: Introductionmentioning
confidence: 99%
“…The unilateral nature of this interaction (feet can only push on the ground) limits the motion that a legged robot can realize and plays a crucial role in its stability. When walking on a flat ground, this corresponds to having the Center of Pressure (CoP) stay within the support polygon [25]. Model Predictive Control (MPC) is one of few suitable methods to handle such constraints [17], and has been used therefore extensively for the control of legged robots.…”
Section: Introductionmentioning
confidence: 99%
“…These sources of uncertainty can always be reduced with more precise (and more expensive) hardware or we can try to estimate them, but only up to a point: there always remains a certain amount of uncertainty. And as a result, there always remains a certain amount of tracking error when trying to follow a reference motion [5], [12], [9], [25], [15]. In order to satisfy all constraints in the presence of such tracking error, the usual approach is to introduce hand tuned safety margins [24].…”
Section: Introductionmentioning
confidence: 99%
“…Methods to make robots walk [1], run [2] and jump [3] exist and they are well understood [4]. However, such methods are usually specifically designed for a given task and robot morphology.…”
Section: Introductionmentioning
confidence: 99%