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相关论文: A Benchmarking of DCM Based Architectures for Posi…

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This paper contributes towards the development and comparison of Divergent-Component-of-Motion (DCM) based control architectures for humanoid robot locomotion. More precisely, we present and compare several DCM based implementations of a…

机器人学 · 计算机科学 2019-11-28 Giulio Romualdi , Stefano Dafarra , Yue Hu , Daniele Pucci

In this paper, previous works on the Model Predictive Control (MPC) and the Divergent Component of Motion (DCM) for bipedal walking control are extended. To this end, we employ a single MPC which uses a combination of Center of Pressure…

机器人学 · 计算机科学 2017-03-01 Milad Shafiee-Ashtiani , Aghil Yousefi-Koma , Masoud Shariat-Panahi

Generating robust locomotion for a humanoid robot in the presence of disturbances is difficult because of its high number of degrees of freedom and its unstable nature. In this paper, we used the concept of Divergent Component of…

机器人学 · 计算机科学 2021-12-23 Mohammadreza Kasaei , Nuno Lau , Artur Pereira

A common approach to the generation of walking patterns for humanoid robots consists in adopting a layered control architecture. This paper proposes an architecture composed of three nested control loops. The outer loop exploits a robot…

We present a computationally efficient method for online planning of bipedal walking trajectories with push recovery. In particular, the proposed methodology fits control architectures where the Divergent-Component-of-Motion (DCM) is…

Keeping the stability can be counted as the essential ability of a humanoid robot to step out of the laboratory to work in our real environment. Since humanoid robots have similar kinematic to a human, humans expect these robots to be…

机器人学 · 计算机科学 2019-11-19 Mohammadreza Kasaei , Nuno Lau , Artur Pereira

Jumping can be an effective way of locomotion to overcome small terrain gaps or obstacles. In this paper we propose two different approaches to perform jumps with a humanoid robot. Specifically, starting from a pre-defined CoM trajectory we…

机器人学 · 计算机科学 2022-07-06 Fabio Bergonti , Luca Fiorio , Daniele Pucci

Walking motion planning based on Divergent Component of Motion (DCM) and Linear Inverted Pendulum Model (LIPM) is one of the alternatives that could be implemented to generate online humanoid robot gait trajectories. This algorithm requires…

Dynamic legged locomotion is a challenging topic because of the lack of established control schemes which can handle aerial phases, short stance times, and high-speed leg swings. In this paper, we propose a controller combining whole-body…

机器人学 · 计算机科学 2019-09-17 Donghyun Kim , Jared Di Carlo , Benjamin Katz , Gerardo Bledt , Sangbae Kim

Locomotion of legged machines faces the problems of model complexity and computational costs. Algorithms based on complex models and/or reinforcement learning exist to solve the walking control task. In this project, we aim to develop a…

机器人学 · 计算机科学 2018-05-17 Kendeas Theofanous

Humans can balance very well during walking, even when perturbed. But it seems difficult to achieve robust walking for bipedal robots. Here we describe the simplest balance controller that leads to robust walking for a linear inverted…

机器人学 · 计算机科学 2022-11-14 Linqi Ye , Xueqian Wang , Houde Liu , Bin Liang

The computational power of mobile robots is currently insufficient to achieve torque level whole-body Model Predictive Control (MPC) at the update rates required for complex dynamic systems such as legged robots. This problem is commonly…

机器人学 · 计算机科学 2019-08-12 Ruben Grandia , Farbod Farshidian , René Ranftl , Marco Hutter

The humanoid robot iCub is a research platform of the Fondazione Istituto Italiano di Tecnologia (IIT), spread among different institutes around the world. In the most recent version of iCub, the robot is equipped with stronger legs and…

机器人学 · 计算机科学 2017-07-18 Yue Hu , Jorhabib Eljaik , Kevin Stein , Francesco Nori , Katja Mombaur

In this paper, a method for stabilizing biped robots stepping by a combination of Divergent Component of Motion (DCM) tracking and step adjustment is proposed. In this method, the DCM trajectory is generated, consistent with the predefined…

This paper presents a layered control approach for real-time trajectory planning and control of robust cooperative locomotion by two holonomically constrained quadrupedal robots. A novel interconnected network of reduced-order models, based…

机器人学 · 计算机科学 2022-11-15 Jeeseop Kim , Randall T Fawcett , Vinay R Kamidi , Aaron D Ames , Kaveh Akbari Hamed

Traditional one-step preview planning algorithms for bipedal locomotion struggle to generate viable gaits when walking across terrains with restricted footholds, such as stepping stones. To overcome such limitations, this paper introduces a…

机器人学 · 计算机科学 2026-02-20 Zhaoyang Xiang , Victor Paredes , Guillermo A. Castillo , Ayonga Hereid

One of the challenges for the robotics community is to deploy robots which can reliably operate in real world scenarios together with humans. A crucial requirement for legged robots is the capability to properly balance on their feet,…

机器人学 · 计算机科学 2017-05-31 Stefano Dafarra , Francesco Romano , Francesco Nori

A whole-body torque control framework adapted for balancing and walking tasks is presented in this paper. In the proposed approach, centroidal momentum terms are excluded in favor of a hierarchy of high-priority position and orientation…

机器人学 · 计算机科学 2017-07-27 Marie Charbonneau , Gabriele Nava , Francesco Nori , Daniele Pucci

We introduce a robust control architecture for the whole-body motion control of torque controlled robots with arms and legs. The method is based on the robust control of contact forces in order to track a planned Center of Mass trajectory.…

机器人学 · 计算机科学 2018-01-31 Farbod Farshidian , Edo Jelavić , Alexander W. Winkler , Jonas Buchli

We present an integrated approach to locomotion and balancing of humanoid robots based on direct centroidal control. Our method uses a five-mass description of a humanoid. It generates whole-body motions from desired foot trajectories and…

机器人学 · 计算机科学 2022-08-10 Grzegorz Ficht , Sven Behnke
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