ROBOTRAN: a powerful symbolic gnerator of multibody models

Docquier, Nicolas; Poncelet, Antoine; Paul, Friedemann

doi:10.5194/ms-4-199-2013

Cited by 56 publications

(25 citation statements)

References 17 publications

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“…In detail we considered stepping on elevated surfaces (50 cm), large stepping (65 cm), squatting and swaying with 50 kg weight, landing on a single foot from 0.35 m, reactive stepping (forward and lateral) and falling (forward and lateral). The simulations were performed with an open source compliant joint simulator based on Robotran multibody modeling tool [16]. More details on these tasks and specification results can be found in a related work [17].…”

Section: Design For Robustnessmentioning

confidence: 99%

WALK-MAN humanoid lower body design optimization for enhanced physical performance

Negrello

Garabini

Catalano

et al. 2016

2016 IEEE International Conference on Robotics and Automation (ICRA)

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The deployment of robots to assist in environments hostile for humans during emergency scenarios require robots to demonstrate enhanced physical performance, that includes adequate power, adaptability and robustness to physical interactions and efficient operation. This work presents the design and development of the lower body of the new high performance humanoid WALK-MAN, a robot developed recently to assist in disaster response scenarios. The paper introduces the details of the WALK-MAN lower-body, highlighting the innovative design optimization features considered to maximize the leg performance. Starting from the general lower body specifications the objectives of the design and how they were addressed are introduced, including the selection of the leg kinematics, the arrangement of the actuators and their integration with the leg structure to maximize the range of motion, reduce the leg mass and inertia, and shape the leg mass distribution for better dynamic performance. Physical robustness is ensured with the integration of elastic transmission and impact energy absorbing covers. Experimental walking trials demonstrate the correct operation of the legs while executing a walking gait

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Section: Design For Robustnessmentioning

confidence: 99%

WALK-MAN humanoid lower body design optimization for enhanced physical performance

Negrello

Garabini

Catalano

et al. 2016

2016 IEEE International Conference on Robotics and Automation (ICRA)

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“…showed that trajectory optimization of gait for a quadrupedal robot modeled with RobCoGen was five times faster with AD than with FD [27]. Other packages for robotic applications with modules supporting AD include Drake [28], Robotran [29], MBSlib [30], and Pinocchio [31]. Drake is a collection of tools that relies on Eigen [32] for linear algebra.…”

Section: Introductionmentioning

confidence: 99%

Algorithmic differentiation improves the computational efficiency of OpenSim-based trajectory optimization of human movement

et al. 2019

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Algorithmic differentiation (AD) is an alternative to finite differences (FD) for evaluating function derivatives. The primary aim of this study was to demonstrate the computational benefits of using AD instead of FD in OpenSim-based trajectory optimization of human movement. The secondary aim was to evaluate computational choices including different AD tools, different linear solvers, and the use of first-or second-order derivatives. First, we enabled the use of AD in OpenSim through a custom source code transformation tool and through the operator overloading tool ADOL-C. Second, we developed an interface between OpenSim and CasADi to solve trajectory optimization problems. Third, we evaluated computational choices through simulations of perturbed balance, two-dimensional predictive simulations of walking, and three-dimensional tracking simulations of walking. We performed all simulations using direct collocation and implicit differential equations. Using AD through our custom tool was between 1.8 ± 0.1 and 17.8 ± 4.9 times faster than using FD, and between 3.6 ± 0.3 and 12.3 ± 1.3 times faster than using AD through ADOL-C. The linear solver efficiency was problem-dependent and no solver was consistently more efficient. Using second-order derivatives was more efficient for balance simulations but less efficient for walking simulations. The walking simulations were physiologically realistic. These results highlight how the use of AD drastically decreases computational time of trajectory optimization problems as compared to more common FD. Overall, combining AD with direct collocation and implicit differential equations decreases the computational burden of trajectory optimization of human movement, which will facilitate their use for biomechanical applications requiring the use of detailed models of the musculoskeletal system. Algorithmic differentiation speeds up trajectory optimization of human movement PLOS ONE | https://doi.Fig 2.Flowchart depicting the optimal control framework. We developed two approaches (AD-ADOLC and AD-Recorder) to make an OpenSim function F and its forward (F fwd) and reverse (F rev) directional derivatives available within the CasADi environment for use by the NLP solver during the optimization. In the AD-ADOLC approach (top), ADOL-C's algorithms are used in a C++ code to provide F fwd and F rev. In the AD-Recorder approach (bottom), Recorder provides the expression graph of F as MATLAB source code from which CasADi's C-code generator generates C-code containing F, F fwd, and F rev. The AD-Recorder approach combines operator overloading, when generating the expression graph, and source code transformation, when processing the expression graph to generate C-code for F, F fwd, and F rev. In both approaches, the code comprising F, F fwd, and F rev is compiled as a Dynamic-link Library (DLL), which is imported as an external function within the CasADi environment. In our application, F represents the multi-body dynamics and is called when formulating the optimal control problem. The latte...

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“…In order to model contact interactions between multibody systems and granular media, the NSCD formalism is extended to the equations of motion of articulated chains. In the proposed approach, the configuration of the latter is described using relative coordinates, according to the methodology detailed in [26,27]. Therefore, for a tree-like system (i.e., without any kinematic loop), the dynamics equation for a smooth motion without contact does not involve constraint equations and can be formulated as follows:…”

Section: Nscd Extension To Mbsmentioning

confidence: 99%

Modelling and simulation of coupled multibody systems and granular media using the non-smooth contact dynamics approach

Docquier

Lantsoght

Dubois³

et al. 2020

Multibody Syst Dyn

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HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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ROBOTRAN: a powerful symbolic gnerator of multibody models

Cited by 56 publications

References 17 publications

WALK-MAN humanoid lower body design optimization for enhanced physical performance

WALK-MAN humanoid lower body design optimization for enhanced physical performance

Algorithmic differentiation improves the computational efficiency of OpenSim-based trajectory optimization of human movement

Modelling and simulation of coupled multibody systems and granular media using the non-smooth contact dynamics approach

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