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We present a new walking foot-placement controller based on 3LP, a 3D model of bipedal walking that is composed of three pendulums to simulate falling, swing and torso dynamics. Taking advantage of linear equations and closed-form solutions…

Robotics · Computer Science 2018-11-12 Salman Faraji , Philippe Muellhaupt , Auke J. Ijspeert

In this paper, an online adaptation algorithm for bipedal walking on uneven surfaces with height uncertainty is proposed. In order to generate walking patterns on flat terrains, the trajectories in the task space are planned to satisfy the…

Robotics · Computer Science 2017-03-31 Majid Khadiv , S. Ali. A. Moosavian , Aghil Yousefi-Koma , Hessam Maleki , Majid Sadedel

Motion imitation is a pivotal and effective approach for humanoid robots to achieve a more diverse range of complex and expressive movements, making their performances more human-like. However, the significant differences in kinematics and…

Robotics · Computer Science 2025-08-04 Zhenghan Chen , Haodong Zhang , Dongqi Wang , Jiyu Yu , Haocheng Xu , Yue Wang , Rong Xiong

For a robot to be both autonomous and collaborative requires the ability to adapt its movement to a variety of external stimuli, whether these come from humans or other robots. Typically, legged robots have oscillation periods explicitly…

Robotics · Computer Science 2023-07-03 Alex Szorkovszky , Frank Veenstra , Kyrre Glette

We have been developing human-sized biped robots based on passive dynamic mechanisms. In human locomotion, the muscles activate at the same rate relative to the gait cycle during running. To achieve adaptive running for robots, such…

Robotics · Computer Science 2024-03-15 Yusuke Sakurai , Tomoya Kamimura , Yuki Sakamoto , Shohei Nishii , Kodai Sato , Yuta Fujiwara , Akihito Sano

Bipedal robots are a prime example of systems which exhibit highly nonlinear dynamics, underactuation, and undergo complex dissipative impacts. This paper discusses methods used to overcome a wide variety of uncertainties, with the end…

Optimization and Control · Mathematics 2018-10-04 Shishir Kolathaya , Jacob Reher , Aaron D. Ames

In this work, we demonstrate robust walking in the bipedal robot Digit on uneven terrains by just learning a single linear policy. In particular, we propose a new control pipeline, wherein the high-level trajectory modulator shapes the…

Current approaches to humanoid control generally fall into two paradigms: perceptive locomotion, which handles terrain well but is limited to pedal gaits, and general motion tracking, which reproduces complex skills but ignores…

Robotics · Computer Science 2026-01-13 Ziwen Zhuang , Shaoting Zhu , Mengjie Zhao , Hang Zhao

We show dynamic locomotion strategies for wheeled quadrupedal robots, which combine the advantages of both walking and driving. The developed optimization framework tightly integrates the additional degrees of freedom introduced by the…

The contact sequence of humanoid walking consists of single and double support phases (SSP and DSP), and their coordination through proper duration and dynamic transition based on the robot's state is crucial for maintaining walking…

Robotics · Computer Science 2026-01-06 Kwanwoo Lee , Gyeongjae Park , Myeong-Ju Kim , Jaeheung Park

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…

Quadruped locomotion is rapidly maturing to a degree where robots now routinely traverse a variety of unstructured terrains. However, while gaits can be varied typically by selecting from a range of pre-computed styles, current planners are…

This paper presents a novel approach to fall prediction for bipedal robots, specifically targeting the detection of potential falls while standing caused by abrupt, incipient, and intermittent faults. Leveraging a 1D convolutional neural…

Robotics · Computer Science 2025-06-03 M. Eva Mungai , Gokul Prabhakaran , Jessy W. Grizzle

Model predictive control (MPC) has shown great success for controlling complex systems such as legged robots. However, when closing the loop, the performance and feasibility of the finite horizon optimal control problem (OCP) solved at each…

Loco-manipulation of quadrupedal robots has broadened robotic applications, but using legs as manipulators often compromises locomotion, while mounting arms complicates the system. To mitigate this issue, we introduce bipedalism for…

Robotics · Computer Science 2025-07-29 Yuyou Zhang , Radu Corcodel , Ding Zhao

Performing highly agile dynamic motions, such as jumping or running on uneven stepping stones has remained a challenging problem in legged robot locomotion. This paper presents a framework that combines trajectory optimization and model…

Robotics · Computer Science 2022-09-20 Chuong Nguyen , Lingfan Bao , Quan Nguyen

Generating stable walking gaits that yield natural locomotion when executed on robotic-assistive devices is a challenging task that often requires hand-tuning by domain experts. This paper presents an alternative methodology, where we…

Robotics · Computer Science 2022-03-16 Kejun Li , Maegan Tucker , Rachel Gehlhar , Yisong Yue , Aaron D. Ames

Performing trajectory design for humanoid robots with high degrees of freedom is computationally challenging. The trajectory design process also often involves carefully selecting various hyperparameters and requires a good initial guess…

Robotics · Computer Science 2024-12-18 Bohao Zhang , Ram Vasudevan

We present a method for humanoid robot walking on partial footholds such as small stepping stones and rocks with sharp surfaces. Our algorithm does not rely on prior knowledge of the foothold, but information about an expected foothold can…

As humanoid robots enter real-world environments, ensuring robust locomotion across diverse environments is crucial. This paper presents a computationally efficient hierarchical control framework for humanoid robot locomotion based on…

Robotics · Computer Science 2025-09-08 Adrian B. Ghansah , Sergio A. Esteban , Aaron D. Ames
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