Robotran-YARP Interface: A Framework for Real-Time Controller Developments Based on Multibody Dynamics Simulations

Habra, Timothee; Dallali, Houman; Cardellino, Alberto; Natale, Lorenzo; Tsagarakis, Nikos G.; Paul, Friedemann; Ronsse, Renaud

doi:10.1007/978-3-319-30614-8_7

Cited by 8 publications

(6 citation statements)

References 25 publications

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“…Despite some discrepancies, the above results (Figures [24][25][26] show that the ROS-ROBOTRAN coupling proposed in this paper allows to develop a haptic key for digital pianos able to reproduce the F haptic action dynamic force quite faithfully, i.e., the goldstandard touch of a grand piano. Moreover, the symbolic multibody modeling approach makes it very easy to modify any physical parameter of the action or even the action itself in the haptic device, to modulate the haptic force accordingly.…”

Section: Figure 23mentioning

confidence: 77%

Haptic Devices Based on Real-Time Dynamic Models of Multibody Systems

Docquier

Timmermans

Paul

2021

Sensors

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Multibody modeling of mechanical systems can be applied to various applications. Human-in-the-loop interfaces represent a growing research field, for which increasingly more devices include a dynamic multibody model to emulate the system physics in real-time. In this scope, reliable and highly dynamic sensors, to both validate those models and to measure in real-time the physical system behavior, have become crucial. In this paper, a multibody modeling approach in relative coordinates is proposed, based on symbolic equations of the physical system. The model is running in a ROS environment, which interacts with sensors and actuators. Two real-time applications with haptic feedback are presented: a piano key and a car simulator. In the present work, several sensors are used to characterize and validate the multibody model, but also to measure the system kinematics and dynamics within the human-in-the-loop process, and to ultimately validate the haptic device behavior. Experimental results for both developed devices confirm the interest of an embedded multibody model to enhance the haptic feedback performances. Besides, model parameters variations during the experiments illustrate the infinite possibilities that such model-based configurable haptic devices can offer.

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Section: Figure 23mentioning

confidence: 77%

Haptic Devices Based on Real-Time Dynamic Models of Multibody Systems

Docquier

Timmermans

Paul

2021

Sensors

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“…This abstraction layer allowed to gradually expose new functionalities as they became available in the hardware platform, with minimal impact to the user code. Thanks to this abstraction layer various iCub simulators have been implemented using different engines [73,46,32]. All these simulators share the same robot interface and can be used interchangeably without modification to the code.…”

Section: The Software Infrastructurementioning

confidence: 99%

Humanoid Robotics: A Reference

2019

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In this chapter we describe the history and evolution of the iCub humanoid platform. We start by describing the first version as it was designed during the RobotCub EU project and illustrate how it evolved to become the platform that is adopted by more than 30 laboratories world-wide. We complete the chapter by illustrating some of the research activities that are currently carried out on the iCub robot, i.e. visual perception, event-driven sensing and dynamic control. We conclude the Chapter with a discussion of the lessons we learned and a preview of the upcoming next release of the robot, iCub 3.0.

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“…The set of robot interfaces are generic and have been implemented various simulators, thus allowing switching control of simulators and the real robot at no cost (Tikhanoff et al, 2008;Mingo et al, 2014;Habra et al, 2015).…”

Section: Robot Interfacementioning

confidence: 99%

The iCub Software Architecture: Evolution and Lessons Learned

et al. 2016

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The complexity of humanoid robots is increasing with the availability of new sensors, embedded CPUs, and actuators. This wealth of technologies allows researchers to investigate new problems like multi-modal sensory fusion, whole-body control and multimodal human-robot interaction. Under the hood of these robots, the software architecture has an important role: it allows researchers to get access to the robot functionalities focusing primarily on their research problems and supports code reuse to minimize development and debugging, especially when new hardware becomes available. But more importantly, it allows increasing the complexity of the experiments that can be carried out before system integration becomes unmanageable, and debugging draws more resources than research itself. In this paper, we illustrate the software architecture of the iCub humanoid robot and the software engineering best practices that have emerged driven by the needs of our research community. We describe the latest development of the middleware supporting interface definition and automatic code generation, logging, ROS compatibility, and channel prioritization. We show the robot abstraction layer and how it has been modified to better address the requirements of the users and to support new hardware as it became available. We also describe the testing framework, and we have recently adopted for developing code using a test-driven methodology. We conclude the paper discussing the lessons we learned during the past 11 years of software development on the iCub humanoid robot.

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Robotran-YARP Interface: A Framework for Real-Time Controller Developments Based on Multibody Dynamics Simulations

Cited by 8 publications

References 25 publications

Haptic Devices Based on Real-Time Dynamic Models of Multibody Systems

Haptic Devices Based on Real-Time Dynamic Models of Multibody Systems

Humanoid Robotics: A Reference

The iCub Software Architecture: Evolution and Lessons Learned

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