Jerk Control of Floating Base Systems with Contact-Stable Parametrised Force Feedback
Ahmad Gazar Gabriele Nava Francisco Javier Andrade Chavez Daniele Pucci
cs.RO









IEEE Transactions on Robotics, Preprint Version. Accepted September, 2020
Shell Gazar, Nava et al.: Jerk Control of Floating Base Systems with Contact-Stable Parametrised Force Feedback


Jerk Control of Floating Base Systems 
 with Contact-Stable Parametrised Force Feedback
    Ahmad Gazar^*,1, Gabriele Nava^*,2,3, Francisco Javier Andrade Chavez^2, Daniele Pucci^2 

^* The two authors equally contributed to this paper.
Manuscript received July 22, 2019; revised February 15, 2020; accepted April 23, 2020.


This paper is supported by EU An.Dy Project. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 731540.  The content of this publication is the sole responsibility of the authors.  The European Commission or its services cannot be held responsible for any use that may be made of the information it contains.
^1 Max Planck Institute for Intelligent Systems, Tübingen, Germany, name.surname@tuebingen.mpg.de
^2 Dynamic Interaction Control, Istituto Italiano di Tecnologia, Genova, Italy name.surname@iit.it
^3 DIBRIS, University of Genova, Genova, Italy
Digital Object Identifier (DOI): see top of this page.
© © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

    
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Nonlinear controllers for floating base systems in contact with the environment are often framed as quadratic programming (QP) optimization problems. Common drawbacks of such QP based controllers are: 

the control input often experiences discontinuities; no force feedback from Force/Torque (FT) sensors installed on the robot is taken into account. This paper attempts to address these limitations 
using jerk based control architectures. 
The proposed controllers assume the rate-of-change of the joint torques as control input, and exploit the system position, velocity, accelerations, and contact wrenches as measurable quantities. The key ingredient of the presented approach is a one-to-one correspondence between free variables and 
an 


inner approximation of 
the manifold defined by the contact stability constraints. 
More precisely, the proposed correspondence covers completely the contact stability manifold except for the so-called friction cone, for which there exists a unique correspondence for more than 90% of its elements.  
The correspondence  allows us to transform the underlying constrained optimisation problem into one that is unconstrained. Then, we propose a jerk control framework that exploits the proposed correspondence and uses FT measurements in the control loop. Furthermore, we present Lyapunov stable controllers for the system momentum in the jerk control framework. The  approach is validated with simulations and experiments using the iCub humanoid robot.






Force Control, Contact Modeling, Jerk Control.













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[
    < g r a p h i c s >
]Ahmad Gazar
Ahmad received his Bachelor degree in 2011 in Engineering and Material Science from the German University in Cairo. He received his master degree in 2018 in Artificial Intelligence and Robotics from La Sapienza University in Rome, after he conducted his master thesis in Dynamic Interaction and Control lab at the Italian Institute of Technology (IIT) in Genova under the supervision of Daniele Pucci. Currently, he is pursuing his PhD in Robust Model Predictive Control for Locomotion of Legged Robots, at the Movement Generation and Control lab, at Max-Planck Institute for Intelligent Systems in Tuebingen under the supervision of Ludovic Righetti and Andrea Del Prete. His main research interests are optimal control, and trajectory optimization for robots with arms and legs using robust and stochastic MPC (Model Predictive Control).





[
    < g r a p h i c s >
]Gabriele Nava
Gabriele received the Bachelor and Master degrees in Mechanical Engineering from Politecnico di Milano, in 2013 and 2015, respectively. In 2020 he earned the PhD title in Bioengineering and Robotics at Università degli Studi di Genova, in cooperation with the Italian Institute of Technology (IIT), under the supervision of Daniele Pucci and Giorgio Metta. He is currently working as postdoc researcher in the Dynamic Interaction Control Lab at IIT. His main research topic concerns the design of control algorithms for floating base systems, with a focus on Aerial Humanoid Robotics. He is the Scrum Master of the iRonCub group, which pursues the objective of making the humanoid robot iCub fly. 





[
    < g r a p h i c s >
]Francisco Andrade
Francisco received his Bachelor degree in Mechantronics Engineering from Universidad Anahuac Mayab, Merida, Mexico in 2011. He received a double Master Degree in Advance Robotics from Università degli Studi di Genova and Ecole Central de Nantes in 2015. He successfully concluded a PhD in Bioengineering and Robotics at Università degli Studi di Genova in cooperation with the Istituto Italiano di Tecnologia (IIT) under the supervision of Daniele Pucci in 2019. From 2019 to 2020, he was a Postdoc in the Dynamic Interaction Control Lab at IIT. During this period, he also held a Scrum Master position, first for the Telexistence group and later for an Industrial Collaboration Project. Francisco Javier Andrade Chavez is currently a PostDoc and lab manager in the Human-Centered Robotics Lab at University of Waterloo, Canada. His main research interests are sensing, estimation, and control of dynamics and its application to bio-inspired robots and human-robot collaboration.





[
    < g r a p h i c s >
]Daniele Pucci
Daniele received the bachelor and master degrees in Control Engineering with highest honors from ”Sapienza”, University of Rome, in 2007 and 2009, respectively. In 2009, he also received the ”Academic Excellence Award” from Sapienza. In 2013, he earned the PhD title in Nonlinear control applied to Flight Dynamics, with a thesis prepared at INRIA Sophia Antipolis, France, under the supervision of Tarek Hamel and Claude Samson. From 2013 to 2017, he has been a postdoc at the Istituto Italiano di Tecnologia (IIT) working within the EU project CoDyCo. Since August 2017, he is the head of the Dynamic Interaction Control lab.  The main lab research focus is on the humanoid robot locomotion problem, with specific attention on the control and planning of the associated nonlinear systems. Also, the lab is pioneering Aerial Humanoid Robotics, whose main aim is to make flying humanoid robots. Currently, the lab is implementing iRonCub, the jet-powered flying version of the humaonid robot iCub. Daniele is also the scientific PI of the H2020 European Project AnDy, task leader of the H2020 European Project SoftManBot, and coordinator of the joint laboratory between IIT and Honda JP. In 2019, he was awarded as Innovator of the year Under 35 Europe from the MIT Technology Review magazine. Since 2020 and in the context of the split site PhD supervision program, Daniele is a visiting lecturer at University of Manchester.



















