Balanced Walking with Capture Steps

Missura, Marcell; Behnke, Sven

doi:10.1007/978-3-319-18615-3_1

Cited by 13 publications

(7 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In earlier work, we evaluated the same capture step controller with our robot Dynaped [Missura and Behnke, 2015b]. The video f shows reliable and controllable walking skills with strong disturbance rejection capabilities.…”

Section: Dynaped Videosmentioning

confidence: 99%

Capture Steps: Robust Walking for Humanoid Robots

Missura

Bennewitz

Behnke

2019

Int. J. Human. Robot.

Self Cite

View full text Add to dashboard Cite

Stable bipedal walking is a key prerequisite for humanoid robots to reach their potential of being versatile helpers in our everyday environments. Bipedal walking is, however, a complex motion that requires the coordination of many degrees of freedom while it is also inherently unstable and sensitive to disturbances. The balance of a walking biped has to be constantly maintained. The most effective ways of controlling balance are well timed and placed recovery steps — capture steps — that absorb the expense momentum gained from a push or a stumble. We present a bipedal gait generation framework that utilizes step timing and foot placement techniques in order to recover the balance of a biped even after strong disturbances. Our framework modifies the next footstep location instantly when responding to a disturbance and generates controllable omnidirectional walking using only very little sensing and computational power. We exploit the open-loop stability of a central pattern generated gait to fit a linear inverted pendulum model (LIPM) to the observed center of mass (CoM) trajectory. Then, we use the fitted model to predict suitable footstep locations and timings in order to maintain balance while following a target walking velocity. Our experiments show qualitative and statistical evidence of one of the strongest push-recovery capabilities among humanoid robots to date.

show abstract

Section: Dynaped Videosmentioning

confidence: 99%

Capture Steps: Robust Walking for Humanoid Robots

Missura

Bennewitz

Behnke

2019

Int. J. Human. Robot.

Self Cite

View full text Add to dashboard Cite

show abstract

“…7. The step timing is computed using the capture step framework [13], based on the lateral CoM state [14].…”

Section: Bipedal Walkingmentioning

confidence: 99%

RoboCup 2016 Humanoid TeenSize Winner NimbRo: Robust Visual Perception and Soccer Behaviors

Farazi

Allgeuer

Ficht

et al. 2017

RoboCup 2016: Robot World Cup XX

Self Cite

View full text Add to dashboard Cite

The trend in the RoboCup Humanoid League rules over the past few years has been towards a more realistic and challenging game environment. Elementary skills such as visual perception and walking, which had become mature enough for exciting gameplay, are now once again core challenges. The field goals are both white, and the walking surface is artificial grass, which constitutes a much more irregular surface than the carpet used before. In this paper, team NimbRo TeenSize, the winner of the TeenSize class of the RoboCup 2016 Humanoid League, presents its robotic platforms, the adaptations that had to be made to them, and the newest developments in visual perception and soccer behaviour.

show abstract

“…The Linear Inverted Pendulum [13] and the Capture Point [14] models represent two widespread simplified robot models. These simplified linear models have allowed on-line RHC, also providing references for the footstep locations [15], [16], [17].…”

Section: Introductionmentioning

confidence: 99%

“…Differently from [10], we do not fix the robot velocity. Compared to [15], [16], [17], we do not assume the robot to be always in single support. As a consequence, the robot avoids to step in place continuously if the desired robot position does not change, or changes slowly.…”

Section: Introductionmentioning

confidence: 99%

A Control Architecture with Online Predictive Planning for Position and Torque Controlled Walking of Humanoid Robots

Dafarra

Nava

Charbonneau

et al. 2018

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

View full text Add to dashboard Cite

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 kinematic model to plan the footstep positions. In the mid layer, a predictive controller generates a Center of Mass trajectory according to the well-known table-cart model. Through a whole-body inverse kinematics algorithm, we can define joint references for position controlled walking. The outcomes of these two loops are then interpreted as inputs of a stack-of-task QP-based torque controller, which represents the inner loop of the presented control architecture. This resulting architecture allows the robot to walk also in torque control, guaranteeing higher level of compliance. Real world experiments have been carried on the humanoid robot iCub.

show abstract

Balanced Walking with Capture Steps

Cited by 13 publications

References 16 publications

Capture Steps: Robust Walking for Humanoid Robots

Capture Steps: Robust Walking for Humanoid Robots

RoboCup 2016 Humanoid TeenSize Winner NimbRo: Robust Visual Perception and Soccer Behaviors

A Control Architecture with Online Predictive Planning for Position and Torque Controlled Walking of Humanoid Robots

Contact Info

Product

Resources

About