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Workshop Details
Workshop I
- Workshop Details
Open-Source Robotics: Status and Future Horizons

In this half-day workshop, we would like to provide young researchers with an introduction to the state-of-the-art open-source software and hardware available for robotics research, with a special emphasis on locomotion and manipulation problems.

Organizers: Majid Khadiv (Max Planck Institute, Germany), Farbod Farshidian (ETH, Zurich)

Each slot will be 45 min, with 30-40 minutes dedicated to the speaker's presentation and the rest is Q&A.

Pinocchio, an open source and generic purposed library

Dr. Justin Carpentier, INRIA, France

In this talk, I will introduce Pinocchio, an open source and generic purposed library to efficiently compute the dynamics and related quantities to control robots. While many alternative solutions have been developed in the past decade within the robotics community, Pinocchio presents unique features essential for motion planning, optimal control and reinforcement learning in Robotics. Pinocchio is nowadays word-widely used in both industry and academia. During this talk, I will notably expose some new recent features of Pinocchio, namely the efficient and robust resolution of constrained dynamic equations and the analytical derivatives of Rigid Body Dynamics algorithms. I will also depict the future roadmap of the project and related software.

Task-Space Inverse Dynamics: a C++ Library for Efficient Whole-Body Control

Dr. Andrea Del Prete, University of Trento, Italy

In the last decade Task-Space Inverse Dynamics (TSID) has become a standard method for the control of complex robots, especially quadrupeds and bipeds. However, while the theoretical aspects of this control framework have reached maturity and a large consensus in the robotics community, a shared implementation was missing. The TSID library was created in 2017 with the goal of overcoming this limitation. TSID is an efficient, generic and open-source C++ library based on Eigen (for linear algebra), Pinocchio (for multi-body dynamics) and Eiquadprog (for solving quadratic programs). It comes with Python bindings to ease prototyping and Debian packages to ease the installation process. TSID is the result of a collaborative effort by several researchers and engineers from different institutions and universities around the world, and it is currently supported by this active community.

Open Software and Hardware for high-performance legged locomotion

Dr. Majid Khadiv, Max Planck Institute for Intelligent Systems, Germany

Legged robots (especially humanoids) are the most suitable robot platform that could be deployed in our daily lives in the future. However, the complexity in the mechanical structure of these robots as well as the need for advanced control software hindered progress in this field. On the hardware side, there is no standard hardware such that researchers can use to benchmark and compare their algorithms. Furthermore, legged robots are expensive and not every lab can afford to buy them for research. On the control side, the dynamics of these robots are highly complex which makes their control extremely challenging. This complexity has several aspects: 1) These robots are under-actuated and could easily fall down if not controlled properly, 2) locomotion can only be realized through establishing and breaking contact which enforces a hybrid dynamics, 3) The system is very high dimensional (up to 100 states and 50 control inputs) and the dynamic model is highly nonlinear, 4) the system is extremely constrained due to the limited amount of contact forces between the robot and the environment, etc. In this talk, I will first briefly present our recent efforts in the Open Dynamic Robot Initiative (ODRI) to provide the community with low-cost, but high-performance legged platforms that are fully open-source and can be replicated quickly using 3D-printing technology. I will also extensively talk about my recent efforts to find tractable ways on the use of optimal control to safely control legged robots and the corresponding open-source software we developed as a result of this effort.

Electronic architecture of the "Open Dynamic Robot Initiative" platforms, a fully open hardware approach

Dr. Thomas Flayols, LAAS-CNRS, Toulous, France

In this presentation, I will discuss the electronic structure of ODRI robots. Based on custom developed solutions, an open hardware design allows us to intervene at all levels and make our platforms evolve. Modular electronics enable us to build different legged robots thanks to miniaturized permanent magnet synchronous motor controllers and centralization electronics that allows us to close the control loop with a powerful remote computer via a 1kHz wired or wireless link, while keeping the weight of the robots in motion as light as possible.

Open source software for motion planning of legged robots: The NDcurves library and SL1M.

Dr. Steve Tonneau, University of Edinburgh, UK

Making a legged robot walk requires a variety of skills, involving among other things advanced numerical mathematics, software engineering and mechanics. Several recent contributions have attempted provided the community with essential software bricks that are generic enough to be deployed with arbitrary robots. The pinocchio library is a successful example of such contribution for computing the inverse dynamics of the robot. Although generic motion planning frameworks exist, few open source contributions propose to automatically compute the footsteps plans that describe the contacts a robot must create with the environment to move. As a result the contact plans are often manually provided when conducting experiments. In this talk I will introduce SL1M, a python-interfaced combinatorial planner for computing footsteps for legged robots with any number of legs. The library is successfully used by academicians from the Memmo European project[3], but also by SMEs such as the Toulouse-based startup Nimble One[4]. In the second part of the presentation, I will introduce NDcurves[2], a template-based Library for creating curves of arbitrary order and dimension, eventually subject to derivative constraints. I will demonstrate how it can efficiently be used to solve numerical optimisation problems thanks to its automatic differentiation features. Both libraries are available as binaries for Ubuntu.

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Dr. Farbod Farshidian, Robotic System Lab, ETH Zurich.

Recent progress on Crocoddyl, predictive control and codesign

Dr. Carlos Mastalli, University of Edinburgh and Alan Turing Institute, UK

The Crocoddyl project aims to make advances in optimal control that potentially enable various applications such as predictive control and codesign in robotics. In this talk, I will give an overview of the salient aspects of Crocoddyl, share recent progress on numerical optimal control, and report recent examples on predictive control and codesign for agile manoeuvres in legged robotics.

Open-Source Robotics Benchmarks for Developing Neural Causal Models & Results from the Real Robot Challenge

Dr. Stefan Bauer, KTH, Sweden

Many questions in everyday life as well as in research are causal in nature: How would the climate have changed had we reduced our carbon emissions in the 80s? Will my headache go away if I take an aspirin? Inherently, such questions need to specify the causal variables relevant to the question. A central problem for AI and key application areas like health care or robotics is thus the discovery of high-level causal variables from low-level observations like pixel values. While deep neural networks have achieved outstanding success in learning powerful representations for prediction, they fail to explain the effect of interventions. This is reflected in a limited ability to transfer and generalize even between related tasks. As a way forward to learn causal representations from data, this talk will describe our recent advances of combining interventions and causal structure with deep learning based approaches, as well as our efforts to create real-world benchmarks for the interactive learning paradigm. Using the developed open-source benchmarks we organized a robotics challenge in the cloud for dexterous manipulation in 2020 and 2021 and will discuss insights and results from the competition.

Workshop Presenters
Workshop I
- Workshop Presenters
Open-Source Robotics: Status and Future Horizons

Dr. Majid Khadiv, Max Planck Institute for Intelligent Systems, Germany

Majid Khadiv is a postdoc scholar in the Movement Generation and Control Group, at the Max Planck Institute for Intelligent Systems. His research focuses on both theoretical and empirical aspects of locomotion. He is mostly interested in generating complex motions for legged robots using optimization and evaluating these behaviors on real robots. Before joining Movement Generation and Control Group as a postdoc, he visited the Autonomous Motion Department as a PhD visitor and worked on generating robust walking patterns for the humanoid robot Athena. Majid received his BSc in mechanical engineering from Isfahan University of Technology, and his MSc, and Ph.D. from K. N. Toosi University of Technology in 2012 and 2017. From 2012 to 2015, he was acting as the head of the dynamics and control group in the Iranian national humanoid robot project, SURENA III.

Dr. Farbod Farshidian, Robotic System Lab, ETH Zurich.

Dr. Farbod Farshidian is a postdoctoral research assistant at Robotic System Lab, ETH Zurich. In his research, he focuses on the motion planning and control of the mobile robots, with the aim of developing algorithms and techniques that can endow robotic platforms to operate autonomously in real-world applications. Farbod received his BSc and MSc in electrical engineering from K. N. Toosi University of Technology and the University of Tehran in Iran from 2005 to 2012. He got his Ph.D. from ETH Zurich in 2017 on motion planning and control of legged systems. Since January 2018, he is a postdoctoral fellow at Robotic System Lab, ETH Zurich.

Dr. Andrea Del Prete, University of Trento, Italy

Since 2019 Andrea has been a tenure-track assistant professor (RTD-B) in the Industrial Engineering Department of the University of Trento (Italy), where he is teaching robotics and computer programming in C++. In 2018 he had been a research scientist in the Movement Generation and Control group at the Max-Planck Institute for Intelligent Systems (Tübingen, Germany), under the lead of Ludovic Righetti. From 2014 to 2017 he had been an associated researcher in the Gepetto team (LAAS-CNRS, Toulouse), where he has been working with the humanoid robot HRP-2. Before going to LAAS he had spent four years (3 of PhD + 1 of post-doc) at the Italian Institute of Technology (IIT, Genova, Italy), where he had been working on the iCub humanoid robot.

Dr. Carlos Mastalli, University of Edinburgh and Alan Turing Institute, UK

Carlos Mastalli is a Research Associate in the University of Edinburgh and Alan Turing Institute. He leads the steering committee of Crocoddyl and the development of predictive control in the EU MEMMO and ORCA projects. He completed his Ph.D in legged locomotion on challenging terrain at IIT, and has worked in different European research institutions. His research aims to find computational principles for building general motor intelligence in robotics.

Dr. Thomas Flayols, LAAS-CNRS, Toulous, France

Thomas Flayols is a post-doc at LAAS-CNRS in the Gepetto group, where he graduated from his PhD in 2018. Before that, he graduated from Ecole Normale Supérieure de Cachan with a Master Degree in Embedded Systems and Industrial Computing. His research interest focuses on force control of legged robots for locomotion and stabilization. He has a particular interest in experimental validation of estimation and control techniques. He is also a mechatronic engineer attached to open hardware design applied to actuation and perception for robotic. Currently, he is actively contributing to the design of the open-source quadruped robot SOLO initiated by the MPI of Tübingen.

Dr. Steve Tonneau, University of Edinburgh, UK

Steve Tonneau is a lecturer at the University of Edinburgh. He defended his Phd in 2015 after 3 years in the INRIA/IRISA Mimetic research team, and pursued a post-doc in robotics at LAAS-CNRS in Toulouse, within the Gepetto team. His research focuses on motion planning based on the biomechanical analysis of motion invariants. Applications include computer graphics animation as well as robotics.

Dr. Stefan Bauer, KTH, Sweden

Stefan Bauer is currently a research visitor at MILA and a CIFAR Azrieli Global Scholar. Using and developing tools of causality, deep learning and real robotic systems, his research focuses on the longstanding goal of artificial intelligence to design machines that can extrapolate experience across environments and tasks. He obtained his PhD in Computer Science from ETH Zurich and was awarded with the ETH medal for an outstanding doctoral thesis. Before that, he graduated with a BSc and MSc in Mathematics from ETH Zurich and a BSc in Economics and Finance from the University of London (LSE). During his studies, he held scholarships from the Swiss and German National Merit Foundation. In 2019, he won the best paper award at the International Conference of Machine Learning (ICML) and in 2020, he was the lead organizer of the real-robot-challenge.com, a robotics challenge in the cloud.

Dr. Justin Carpentier, INRIA, France

Justin Carpentier is a permanent researcher between Inria and the Computer Science department of École Normale Supérieure in Paris and he is also affiliated with the Prairie Institute (PaRis AI Research InstitutE). Justin's research lies at the interface of Robotics, Perception, Learning and Control inside the Willow research group. Along with this, Justin is also the main developer of several Robotics software, among them Pinocchio, dedicated to the fast and efficient computations of Rigid Body Dynamics equations together with their analytical derivatives.

In September 2018, Justin joined the Willow research group as a postdoctoral fellow. In 2017, he was a postdoctoral researcher inside the Gepetto research group at LAAS-CNRS in Toulouse, France. From 2014 to 2017, he was a PhD candidate in the same Gepetto research group. At this time, his research was devoted to the understanding of the computational foundations of anthropomorphic locomotion. On the one side, he highlighted some mechanisms underlying bipedalism among human beings. On the other side, he contributed to new mathematical formulations for the locomotion of humanoid robots.

He received his degree in Computer Science and Applied Mathematics with the highest honour from Ecole Normale Supérieure de Paris-Saclay in 2013. In 2014, he was a visiting student inside the Optimization in Robotics and Biomechanics group with Katja Mombaur at the University of Heidelberg, Germany.

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