The HuMAnS toolbox, a homogenous framework for motion capture, analysis and simulation

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1 The HuMAnS toolbox, a homogenous framework for motion apture, analysis and simulation Pierre-Brie Wieber, Florene Billet, Laurene Boissieux, Roger Pissard-Gibollet To ite this version: Pierre-Brie Wieber, Florene Billet, Laurene Boissieux, Roger Pissard-Gibollet. The Hu- MAnS toolbox, a homogenous framework for motion apture, analysis and simulation. International Symposium on the 3D Analysis of Human Movement, 2006, Valeniennes, Frane <inria > HAL Id: inria Submitted on 2 Jun 2009 HAL is a multi-disiplinary open aess arhive for the deposit and dissemination of sientifi researh douments, whether they are published or not. The douments may ome from teahing and researh institutions in Frane or abroad, or from publi or private researh enters. L arhive ouverte pluridisiplinaire HAL, est destinée au dépôt et à la diffusion de douments sientifiques de niveau reherhe, publiés ou non, émanant des établissements d enseignement et de reherhe français ou étrangers, des laboratoires publis ou privés.

2 The HuMAnS toolbox, a homogenous framework for motion apture, analysis and simulation Pierre-Brie Wieber, Florene Billet, Laurene Boissieux, Roger Pissard-Gibollet BIPOP team INRIA Rhône-Alpes St Ismier Cedex, Frane Pierre-Brie.Wieber@inrialpes.fr Abstrat Primarily developed for researh needs in humanoid robotis, the HuMAnS toolbox (for Humanoid Motion Analysis and Simulation) also inludes a biomehanial model of a omplete human body, and proposes a set of versatile tools for the modeling, the apture, the analysis and the simulation of human and humanoid motion. This set of tools is organized as a homogenous framework built on top of the numerial failities of Silab, a free generi sientifi pakage, so as to allow generiity and versatility of use, in the hope to enable a new dialogue between diret and inverse dynamis, motion apture and simulation, all of this in a rih sientifi software environment. Notieably, this toolbox is an open-soure software, distributed under the GPL Liense. Motion apture; Motion analysis; Dynamial simulation; Opensoure software. I. INTRODUCTION Originally developed for humanoid robotis researh, the HuMAnS toolbox (for Humanoid Motion Analysis and Simulation) proposes a wealth of state-of-the-art algorithms from the field of robotis researh for the modeling, the analysis and the simulation of human and humanoid motion. These algorithms allow reonstruting effiiently a motion from measures given by multiple sensors. They allow as well simulating preisely human motion, with a musle model speifially developed for the simulation and ontrol of Funtional Eletri Stimulation [1], and with a speifi emphasis on the preise simulation of the ontat between the feet and the ground. They give aess then to a variety of tools to analyze the kinematis, kinetis and dynamis of these reonstruted or simulated movements. Most notieably, this toolbox is developed on top of the rih (and free!) numerial analysis environment proposed by Silab [2] (an open-soure lone of Matlab ) and arhiteted in order to propose a homogenous and versatile framework, with the idea to enable a new dialogue between diret and inverse dynamis, motion apture and simulation. It is proposed as an open-soure software and distributed under the GNU General Publi Liense in order to indue exterior ontributions. Now, setion II presents the general arhiteture of the toolbox, and the different dynamial models that it inludes so far. Setion III fouses then on its motion apture possibilities, presenting the optial sensors that have been modeled so far, and the possibilities for other motion sensors, together with a brief desription of the orresponding numerial method for reonstruting a motion from their measures. Setion IV is a brief introdution to the kineti and dynami analysis failities, as well as to its simulation apaities, fousing espeially on the problem of ontats between the feet and the ground. Setion V offers finally a brief onlusion, opened towards the new uses that we hope suh a versatile set of numerial tools may offer to the field of biomehanis. II. PRESENTATION OF THE HUMANS TOOLBOX A. General arhiteture First of all, a set of Maple algorithms, based on state-ofthe-art algorithms desribed in [3], have been designed to ompute effiient analytial models of musulo-skeletal dynamis suh as the one presented in the next setion, of motion sensors suh as the optial sensors disussed in setion III.A, and of the different inemati and kineti values of interest to the users. These different analytial models are ompiled as generi C funtions, whih are then linked and made available inside Silab s rih numerial analysis environment. These models an be interonneted and proessed then with the help of Silab s powerful numerial methods in order to propose in a homogenous framework both their simulation and their analysis. This allows for example apturing a motion from various sensors measurements, reonstruting some unobserved physial values, and finally simulating additional virtual experiments fed with these different data. An example of suh a new dialogue between analysis and simulation is presented in Fig. 1, where the walking pattern measured in [4] is exeuted by the biomehanial model presented in the next setion, but in spae, i.e. without gravity and ontat fores: we an observe then a rotation of the body, expression of the nonholonomy effets in its dynamis [5] (the same effets that allow ats to always fall bak on their legs). Of ourse, suh virtual biomehanial experiments would be far muh more ostly to realize in real life.

3 Figure 1. Rotation of the body when exeuting a walking pattern in spae, i.e. without gravity and ontat fores. B. The different dynamial models proposed so far The musulo-skeletal dynamis are essentially split in the HuMAnS toolbox, between the dynamial behavior of the musles on one side, and the skeletal dynamis of the body masses and joints on the other side. Of ourse, those two dynamis are losely interonneted, with fores generated by the musles ating on joint movements, and joint movements strething more or less the musles in return. This separation allows however to develop independently new musle models and new mehanial models of the body, interonneting them at will later. Sine the HuMAnS toolbox has been primarily developed for humanoid robotis researh, most of the models proposed so far in the distribution are models of humanoid robots [6], [7], with eletri motor models instead of musle models, but one biomehanial model of a omplete human body is also inluded. This model proposes 16 joints, as shown in Fig. 2, representing 36 degrees of freedom (with 6 additional degrees of freedom for the translation and rotation of the whole body in spae), with masses and lengths based on [8] and [9]. The only musle model presently proposed in the HuMAnS toolbox is the model primarily developed for the simulation and ontrol of Funtional Eletri Stimulation of paralyzed musles in [1]: ( ) k + $ k 0 u + ( ) F + $ F 0 u + + k L 0 % k = " u + # ' & F = " u + # ' F ( = k s L 0 # " L 0 ( ) This model integrates the stiffness k of the musles and the fores F they generate with respet to their length " and the level of alium ions u reeived by way of neural ontrol. All details onerning this musle model an be found in [1] # # (1) Figure 2. The biomehanial model inluded in the distribution of the HuMAnS toolbox proposes 16 joints (blue dots) for 36 degrees of freedom, and 24 anonial optial markers (red rosses). III. MOTION CAPTURE FROM MULTIPLE SENSORS A. Optial sensors and other motion sensors Optial sensors suh as Vion or OptoTrak devies sensors have been modeled in the HuMAnS toolbox, but as presented in setion II.A, the toolbox provides algorithms to derive new models of motion sensors if neessary. The optial sensors are supposed to give the 3D position of a set of markers attahed to different parts of the body. Their output depends therefore solely on the position and orientation of the different joints of the body. Note that the biomehanial model inluded in the HuMAnS toolbox readily proposes 24 anonial markers, as shown in Fig. 2, whih are suffiient to reonstrut ompletely the posture of the body. B. The reonstrution proess We an observe that no subset of the optial markers presented in Fig. 2 allows to dedue diretly and simply the position and orientation of any speifi part of this biomehanial model. Yet, this whole set of markers allows to dedue the omplete 3D posture of the body thanks to redundany in the information present in this whole set of 3D positions. The intelligent use of suh redundany in the sensors measures an only be realized by a global approah, making use of all the knowledge available both in the measures and in the model (what degrees of freedom, oriented in whih diretions ). A simple way to do so is to represent the whole 3D reonstrution proess as a general nonlinear least-squares problem. Powerful algorithms suh as the FSQP algorithm [10]

4 an effiiently solve suh nonlinear problems and propose reliable reonstrutions even when some of the measures are missing, for example beause of olusions. Even real-time treatment is not out of reah: prototypes have already been developed and suessfully tested, though not inluded yet in the toolbox. Suh a generi way of treating the 3D reonstrution proess in motion apture has proved to be extremely powerful and versatile sine missing measures an be dealt with seamlessly, sine measures from ompletely different sensors an be mixed very simply and effiiently, sine additional knowledge onerning the motion being aptured (anonial multi-segmental oordinations for example, or bloked degrees of freedom) an be introdued straightforwardly. IV. ANALYSIS AND SIMULATION TOOLS A. Kinetis and dynamis The motion apture method desribed in the previous setion an be ompletely derived with the only knowledge of the kinematis of the biomehanial model. But for the purpose of analyzing the motion previously aptured or simulating new motions, the HuMAnS toolbox provides many more insights in this model, onerning espeially its kinetis and dynamis. With masses and lengths based on [8] and [9], the toolbox allows to ompute kineti and potential energies in a seond, as well as ontat fores or joint torques, or more simply the position of the enter of mass of the whole body or only of parts of it. Following lassial methods from the robotis researh field, the omplete skeletal dynamis of the biomehanial model (remember the distintion presented in setion II.B) is represented in the HuMAnS toolbox as a Lagrangian dynamis: # M(q) q + N(q, q ) + G(q) = " & % ( + C(q) T ), (2) $ 0' where the vetor q represents the orientation of the joints of the body, q and q their speed and aeleration. The inertia matrix M(q) gathers then in a ompat form all the different inertias of the body, with N(q, q ) all the other inertial nonlinear effets (Coriolis and entrifugal fores), G(q) the gravity effets, " the joint torques generated by the musles, and C(q) T " the ontat fores. More details on these different terms and how they interat an be found in [11] or in any general robotis textbook. All kineti and dynami omputations an be based then on this single representation of the omplete skeletal dynamis. In this framework, for example, the kineti energy of the whole body would simply be: 1 2 q T M(q) q. (3) B. Unilateral ontat fores and simulation of hybrid dynamis The omputation of the ontat fores C(q) T " an be straightforward in the ase of firm grasps: the set of equations (2) is augmented with additional equalities desribing the grasp, and this augmented set of equations an be diretly solved in order to ompute the value of these fores [11]. But the ase of ontats with the environment where one an push but an t pull is unfortunately not as straightforward: they an t be desribed orretly with equalities and need to be desribed with a omplex set of inequalities and omplementarity onditions that is generally referred to as a unilateral ontat [12]. The ombination of the set of equations (2) together with this set of inequalities and omplementarity onditions takes the form of a Nonlinear Complementarity Problem that an be triky to solve in the general ase [12]. The HuMAnS toolbox is therefore speifially equipped with numerial methods dealing effiiently with this omputation, the desription of whih would go far beyond the sope of this publiation: more details on unilateral ontats and how to deal with them an be found then in [12]. Note that on top of the omplexity of solely omputing these unilateral ontat fores, an additional diffiulty arises in their evolution with time. Abrupt hanges an be enountered eah time suh a unilateral ontat is reated or abandoned, for example eah time a foot hits the ground or lifts off. This mix of ontinuous dynamis interlaed with instantaneous abrupt events an be seen as a form of hybrid dynamis. The HuMAnS toolbox proposes then a time-integration sheme speifially rafted to simulate preisely and effiiently suh hybrid dynamis [13]. The point is that suh unilateral ontats leading to hybrid dynamis represent the most usual form of ontat between the feet and the ground: they an be observed therefore in almost every human ativities. Dealing with them properly from a numerial point of view appears then as a mandatory ondition for anybody interested in the numerial analysis of human motion. As we have seen throughout this setion, the HuMAnS toolbox appears to be orretly equipped for suh a task. V. CONCLUSION The HuMAnS toolbox offers tools for the modeling of the kinematis, kinetis and dynamis of human bodies, and for the numerial treatment of these models in motion apture, analysis and simulation. Originating in humanoid robotis researh, all of its algorithms are speifially designed for a maximum of preision and effiieny. A speifi emphasis of the toolbox arhiteture is to allow the user to onnet the different numerial tools at will through the Silab programming language, leading to powerful possibilities in mixing different phases of motion apture, analysis and simulation, a simple example of whih has been shown in Fig.1. We hope this should allow a rih variety of uses in the future for this toolbox in the field of biomehanis. A temporary drawbak is that the only user interfae available so far is at an expert level, implying a good

5 knowledge of both the theory behind motion apture, analysis and simulation, and the tehnialities of numerial software environments suh as Silab (similar to Matlab ). A more user-friendly interfae is now under development. REFERENCES [1] H. El Makssoud, D. Guiraud and P. Poignet, Mathematial musle model for Eletrial Stimulation ontrol strategies, in Pro. IEEE Int. Conf. on Robotis and Automation, New Orleans, LA, USA, April [2] [3] R. Featherstone and D. Orin, Robot Dynamis: Equations and Algorithms in Pro. IEEE Int. Conf. Robotis & Automation, San Franiso, CA, 2000, pp [4] D.A. Winter. Biomehanis and Motor Control of Human Movement, Seond Edition. John Wiley & Sons, New York, [5] P.-B. Wieber, Some omments on the struture of the dynamis of artiulated motion, in Pro. of the Ruperto Carola Symp. on Fast Motions in Biomehanis and Robotis, Heidelberg, sept [6] B. Espiau and P. Sardain, The anthropomorphi biped robot BIP2000, in Pro. IEEE Int. Conf. Robotis & Automation, San Franiso, CA, [7] K. Kaneko et al., Humanoid robot HRP-2, in Pro. IEEE Int. Conf. Robotis & Automation, New Orleans, LA, [8] Zatsiorsky, V. M., Seluyanov, V. N. and Chugunova, L. G. (1990a) Methods of determining mass-inertial harateristis of human body segments. In Contemporary Problems of Biomehanis (Edited by Chemyi G. G. and Regirer, S. A.), pp CRC Press, Massahusetts. [9] P. de Leva, Adjustments to Zatsiorsky-Seluyanov s segment inertia parameters, 3rd ed., vol. 2. Oxford: Clarendon, 1892, pp [10] C.T. Lawrene and A.L. Tits, A Computationally Effiient Feasible Sequential Quadrati Programming Algorithm, SIAM J. Optimization, Vol. 11, No. 4, 2001, pp [11] P.-B. Wieber, Modélisation et ommande d un robot marheur anthropomorphe, PhD thesis, Éole Nationale Supérieure des Mines de Paris, [12] B. Brogliato. Nonsmooth Impat Mehanis. Springer-Verlag, [13] P.-B. Wieber, Hybrid dynamis for the simulation of rehabilitation to walking by FES, in Pro. Int. Symp. on Computer Methods in Biomehanis and Biomedial Engineering, Antibes, Frane, marh 2006.