Online walking gait generation with adaptive foot positioning through Linear Model Predictive control

Diedam, Holger; Dimitrov, Dimitar; Wieber, Pierre-Brice; Mombaur, Katja; Diehl, Moritz

doi:10.1109/iros.2008.4651055

Cited by 159 publications

(139 citation statements)

References 13 publications

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“…One possible way to do this is to use dynamic foot placement taking into account these perturbations. H. DIEDAM et al [17] proposed an algorithm based on the previous paper of P.B. WIEBER [14] that looks promising for such tasks.…”

Section: Discussionmentioning

confidence: 99%

Omni-directional closed-loop walk for NAO

Gouaillier

Collette

Kilner

2010

2010 10th IEEE-RAS International Conference on Humanoid Robots

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Abstract-This paper describes the new walk algorithm implemented on the NAO robot. NAO is a small fully actuated biped robot provided by the French company Aldebaran Robotics. Since the beginning of the company in July 2005, a major goal has been the development of robust walk for the robot. After 5 years of mecatronic design and improvements in robustness of the robot (7 prototypes) and multiple prototypes of humanoid dynamic walk algorithm, an omni-directional walk robust against small obstacles is now available for all the NAO units (more than 700) in the world.

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Section: Discussionmentioning

confidence: 99%

Omni-directional closed-loop walk for NAO

Gouaillier

Collette

Kilner

2010

2010 10th IEEE-RAS International Conference on Humanoid Robots

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“…Using ZMP preview control, high quality hardware [4,5,6] can walk reliably on flat ground. Next generation walking controllers from the ZMP preview family [7,8,9] also consider foot placement in addition to ZMP control either by including the footstep locations in the optimization process, or by using a simplified model to compute a footstep plan online. The approaches that have matured beyond a theoretical state require either precise physical modeling, the estimation of an impact force, or the feedback of a measured ZMP location.…”

Section: Related Workmentioning

confidence: 99%

Balanced Walking with Capture Steps

Missura

Behnke

2015

RoboCup 2014: Robot World Cup XVIII

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Abstract. Bipedal walking is one of the most essential skills required to play soccer with humanoid robots. Superior walking speed and stability often gives teams the winning edge when their robots are the first at the ball, maintain ball control, and drive the ball towards the opponent goal with sure feet. In this contribution, we present an implementation of our Capture Step Framework on a real soccer robot, and show robust omnidirectional walking. The robot not only manages to locomote on an even surface, but can also cope with various disturbances, such as pushes, collisions, and stepping on the feet of an opponent. The actuation is compliant and the robot walks with stretched knees.

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“…Another approach on the control level is model predictive control [7], which iteratively optimizes a cost function for a finite horizon into the future. It has been used in different areas of robotics like tracking mobile robots [8] or generating walking gaits for humanoid robots [9]. Using online replanning methods has many advantages since it extends well-known offline planning methods to dynamic scenarios.…”

Section: A Online Replanningmentioning

confidence: 99%

Reactive phase and task space adaptation for robust motion execution

Englert

Toussaint

2014

2014 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Abstract-An essential aspect for making robots succeed in real-world environments is to give them the ability to robustly perform motions in continuously changing situations. Classical motion planning methods usually create plans for static environments. The direct execution of such plans in dynamic environments often becomes problematic. We present an approach that adapts motion plans by feeding changes of the environment into a transformation of the plan in task space. Furthermore, the progress in the plan is defined with a phase variable that is updated adaptively according to the actual task progress. This phase variable releases the strict time compliance that many motion planning methods bring along. The main benefit of our approach is the ability to do this adaptation in a computational efficient manner during the execution of the motion. Thus, the gap between the motion planning and motion execution stage is bridged by continuously transforming geometric and dynamic features of a reference plan to the current situation. We evaluate the performance of our approach by comparing it to alternative methods such as dynamic motion primitives and continuous replanning on several simulated benchmark tasks. Moreover, we demonstrate the real robot applicability on a PR2 robot platform.

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Online walking gait generation with adaptive foot positioning through Linear Model Predictive control

Cited by 159 publications

References 13 publications

Omni-directional closed-loop walk for NAO

Omni-directional closed-loop walk for NAO

Balanced Walking with Capture Steps

Reactive phase and task space adaptation for robust motion execution

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