Path planning with force-based foothold adaptation and virtual model control for torque controlled quadruped robots

Winkler, Alexander; Havoutis, Ioannis; Bazeille, Stéphane; Ortiz, Jesús; Focchi, Michele; Dillmann, Rüdiger; Semini, Claudio

doi:10.1109/icra.2014.6907815

Cited by 59 publications

(42 citation statements)

References 22 publications

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“…To realize the low-dimensional plan, the controller selects appropriate torque commands, which are computed by the combination of a trunk controller with a joint-space torque controller. The proposed trajectory optimization method increases the locomotion capabilities of our legged robot, compared to our previous framework [6] [7]. As shown in Fig.…”

Section: Introductionmentioning

confidence: 73%

Trajectory and foothold optimization using low-dimensional models for rough terrain locomotion

Mastalli

Focchi

Havoutis

et al. 2017

2017 IEEE International Conference on Robotics and Automation (ICRA)

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Abstract-We present a trajectory optimization framework for legged locomotion on rough terrain. We jointly optimize the center of mass motion and the foothold locations, while considering terrain conditions. We use a terrain costmap to quantify the desirability of a foothold location. We increase the gait's adaptability to the terrain by optimizing the step phase duration and modulating the trunk attitude, resulting in motions with guaranteed stability. We show that the combination of parametric models, stochastic-based exploration and receding horizon planning allows us to handle the many local minima associated with different terrain conditions and walking patterns. This combination delivers robust motion plans without the need for warm-starting. Moreover, we use soft-constraints to allow for increased flexibility when searching in the cost landscape of our problem. We showcase the performance of our trajectory optimization framework on multiple terrain conditions and validate our method in realistic simulation scenarios and experimental trials on a hydraulic, torque controlled quadruped robot.

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Section: Introductionmentioning

confidence: 73%

Trajectory and foothold optimization using low-dimensional models for rough terrain locomotion

Mastalli

Focchi

Havoutis

et al. 2017

2017 IEEE International Conference on Robotics and Automation (ICRA)

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“…The Dynamic Legged Systems Laboratory at IIT recently addressed different aspects of locomotion control, namely, path planning with foothold adaptation, active impedance control, energy-efficient gait generation, stereo-visionassisted locomotion, onboard perception, and local reflex generation (Winkler et al 2014;Semini et al 2013;Bazeille et al 2014;Havoutis et al 2013;Focchi et al 2013). Thus, an integrative action will be taken to combine these technologies on HyQ in a synergistic fashion.…”

Section: Discussionmentioning

confidence: 98%

“…Inserting floating-base inverse dynamics feed-forward terms, Buchli and his collaborators succeed in locomotion control with relatively low servo control gains Winkler et al 2014;Kalakrishnan et al 2011;Boaventura et al 2012). In doing so, they are able to introduce virtual impedance in the joint space, without any requirement of predetermined contact points.…”

Section: Related Work: Control Strategiesmentioning

confidence: 96%

Pattern generation and compliant feedback control for quadrupedal dynamic trot-walking locomotion: experiments on RoboCat-1 and HyQ

et al. 2015

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In this paper, we introduce a method that synergistically combines an analytical pattern generator and a feedback controller frame, which are developed for the purpose of synthesizing dynamic quadrupedal trot-walking locomotion on flat and uneven surfaces. To begin with, the pattern generator analytically produces feasible and dynamically balanced joint motions in accordance with the desired trotwalking characteristics, with no empirical parameter tuning requirements. In concurrence with the pattern generation, a two-phased controller frame is constructed for closed-loop sensory feedback: (i) virtual admittance controller via force sensing, (ii) upper torso angular momentum regulation via gyro sensing. The former controller evaluates joint force errors and generates the corresponding joint displacement Electronic supplementary material The online version of this article (for a given set of virtual spring-damper couples. Together with the position constraints, these displacements are additionally fed-back to local servos for achieving compliant quadrupedal locomotion with which the position/force tradeoff is addressed. The second controller, that is simultaneously used, evaluates the upper torso angular momentum rate change error using measured and reference orientation information. It then regulates the torso orientation in a dynamically consistent way as the rotational inertia is characterized. In order to validate the proposed methodology several experiments are conducted on both flat and uneven surfaces, using two robots with distinct properties; a ∼7 kg cat-sized electrically actuated quadruped (RoboCat-1), and a ∼80 kg Alpine Ibex-sized hydraulically actuated quadruped (HyQ). As a result we demonstrate continuous, repetitive, compliant and dynamically balanced trot-walking cycles in real-robot experiments, adequately confirming the effectiveness of the proposed approach.

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“…legged robots) the set of contact forces and joint commands describe the evolution of the motion. Dynamic maneuvers such as jumping and rearing need to consider different sequences of contacts (mode-switching), which cannot be tackled with traditional predefined gaits [1], [2].…”

Section: Introductionmentioning

confidence: 99%

Hierarchical planning of dynamic movements without scheduled contact sequences

Mastalli

Havoutis

Focchi

et al. 2016

2016 IEEE International Conference on Robotics and Automation (ICRA)

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Abstract-Most animal and human locomotion behaviors for solving complex tasks involve dynamic motions and rich contact interaction. In fact, complex maneuvers need to consider dynamic movement and contact events at the same time. We present a hierarchical trajectory optimization approach for planning dynamic movements with unscheduled contact sequences. We compute whole-body motions that achieve goals that cannot be reached in a kinematic fashion. First, we find a feasible CoM motion according to the centroidal dynamics of the robot. Then, we refine the solution by applying the robot's full-dynamics model, where the feasible CoM trajectory is used as a warm-start point. To accomplish the unscheduled contact behavior, we use complementarity constraints to describe the contact model, i.e. environment geometry and non-sliding active contacts. Both optimization phases are posed as Mathematical Program with Complementarity Constraints (MPCC). Experimental trials demonstrate the performance of our planning approach in a set of challenging tasks.

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Path planning with force-based foothold adaptation and virtual model control for torque controlled quadruped robots

Cited by 59 publications

References 22 publications

Trajectory and foothold optimization using low-dimensional models for rough terrain locomotion

Trajectory and foothold optimization using low-dimensional models for rough terrain locomotion

Pattern generation and compliant feedback control for quadrupedal dynamic trot-walking locomotion: experiments on RoboCat-1 and HyQ

Hierarchical planning of dynamic movements without scheduled contact sequences

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