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In trying to build humanoid robots that perform useful tasks in a world built for humans, we address the problem of autonomous locomotion. Humanoid robot planning and control algorithms for walking over rough terrain are becoming…

In this paper, we present a novel control architecture for the online adaptation of bipedal locomotion on inclined obstacles. In particular, we introduce a novel, cost-effective, and versatile foot sensor to detect the proximity of the…

We propose a robust dynamic walking controller consisting of a dynamic locomotion planner, a reinforcement learning process for robustness, and a novel whole-body locomotion controller (WBLC). Previous approaches specify either the position…

Robotics · Computer Science 2017-08-08 Donghyun Kim , Jaemin Lee , Luis Sentis

Limitations in actuation, sensing, and computation have forced small legged robots to rely on carefully tuned, mechanically mediated leg trajectories for effective locomotion. Recent advances in manufacturing, however, have enabled the…

Robotics · Computer Science 2019-07-02 Neel Doshi , Kaushik Jayaram , Samantha Castellanos , Scott Kuindersma , Robert J Wood

We present an approach for achieving a natural, efficient gait on bipedal robots using straightened legs and toe-off. Our algorithm avoids complex height planning by allowing a whole-body controller to determine the straightest possible leg…

Robotics · Computer Science 2019-08-01 Robert J. Griffin , Georg Wiedebach , Sylvain Bertrand , Alexander Leonessa , Jerry Pratt

In legged locomotion, the relationship between different gait behaviors and energy consumption must consider the full-body dynamics and the robot control as a whole, which cannot be captured by simple models. This work studies the robot…

Robotics · Computer Science 2021-05-04 Christopher McGreavy , Zhibin Li

Planning locomotion trajectories for legged microrobots is challenging because of their complex morphology, high frequency passive dynamics, and discontinuous contact interactions with their environment. Consequently, such research is often…

Legged robots can outperform wheeled machines for most navigation tasks across unknown and rough terrains. For such tasks, visual feedback is a fundamental asset to provide robots with terrain-awareness. However, robust dynamic locomotion…

Balancing oneself using the spine is a physiological alignment of the body posture in the most efficient manner by the muscular forces for mammals. For this reason, we can see many disabled quadruped animals can still stand or walk even…

Robotics · Computer Science 2024-03-05 Yuhong Huang , Zhenshan Bing , Zitao Zhang , Genghang Zhuang , Kai Huang , Alois Knoll

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

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…

Robotics · Computer Science 2021-12-23 Mohammadreza Kasaei , Nuno Lau , Artur Pereira

Multi-legged mobile robots possess high mobility performance in rough terrain environments, stemming from their high postural stability, joint flexibility, and the redundancy provided by multiple legs. In prior research on navigating…

Robotics · Computer Science 2025-10-30 Yusuke Tsunoda , Seiya Yamamoto , Kazuki Ito , Runze Xiao , Keisuke Naniwa , Koichi Osuka

In this paper, we propose an efficient approach to generate dynamic and versatile humanoid walking with non-constant center of mass (COM) height. We exploit the benefits of using reduced order models (ROMs) and stepping control to generate…

Robotics · Computer Science 2020-08-07 Xiaobin Xiong , Aaron Ames

In this work, we introduce a control framework that combines model-based footstep planning with Reinforcement Learning (RL), leveraging desired footstep patterns derived from the Linear Inverted Pendulum (LIP) dynamics. Utilizing the LIP…

Robotics · Computer Science 2024-08-06 Ho Jae Lee , Seungwoo Hong , Sangbae Kim

Robot feet are crucial for maintaining dynamic stability and propelling the body during walking, especially on uneven terrains. Traditionally, robot feet were mostly designed as flat and stiff pieces of metal, which meets its limitations…

Robotics · Computer Science 2024-06-13 Cristina Piazza , Cosimo Della Santina , Giorgio Grioli , Antonio Bicchi , Manuel G. Catalano

This work developed a learning framework for perceptive legged locomotion that combines visual feedback, proprioceptive information, and active gait regulation of foot-ground contacts. The perception requires only one forward-facing camera…

Robotics · Computer Science 2023-02-01 Daniel Chee Hian Tan , Jenny Zhang , Michael , Chuah , Zhibin Li

This study explores the dynamics of asymmetrical bounding gaits in quadrupedal robots, focusing on the integration of torso pitching and hip motion to enhance speed and stability. Traditional control strategies often enforce a fixed…

Robotics · Computer Science 2025-09-01 Jing Cheng , Yasser G. Alqaham , Zhenyu Gan

We focus on the problem of developing energy efficient controllers for quadrupedal robots. Animals can actively switch gaits at different speeds to lower their energy consumption. In this paper, we devise a hierarchical learning framework,…

Robotics · Computer Science 2021-11-23 Yuxiang Yang , Tingnan Zhang , Erwin Coumans , Jie Tan , Byron Boots

For humanoids to be deployed in demanding situations, such as search and rescue, highly intelligent decision making and proficient sensorimotor skill is expected. A promising solution is to leverage human prowess by interconnecting robot…

Robotics · Computer Science 2022-09-16 Guillermo Colin , Youngwoo Sim , Joao Ramos

In this paper, we describe an approach to achieve dynamic legged locomotion on physical robots which combines existing methods for control with reinforcement learning. Specifically, our goal is a control hierarchy in which highest-level…

Robotics · Computer Science 2021-03-15 Kevin Green , Yesh Godse , Jeremy Dao , Ross L. Hatton , Alan Fern , Jonathan Hurst