Auke Ijspeert

Auke Ijspeert is a full professor at the EPFL, and head of the Biorobotics Laboratory (BioRob). He has a B.Sc./M.Sc. in physics from the EPFL (1995), and a PhD in artificial intelligence from the University of Edinburgh (1999). He carried out postdocs at IDSIA and EPFL, and at the University of Southern California (USC). He then became a research assistant professor at USC, and an external collaborator at ATR (Advanced Telecommunications Research institute) in Japan. In 2002, he came back to the EPFL as an SNF assistant professor. He was promoted to associate professor in October 2009 and to full professor in April 2016. His primary affiliation is with the Institute of Bioengineering, and secondary affiliation with the Institute of Mechanical Engineering. His research interests are at the intersection between robotics, computational neuroscience, nonlinear dynamical systems, and machine learning. He is interested in using numerical simulations and robots to get a better understanding of sensorimotor coordination in animals, and in using inspiration from biology to design novel types of robots and adaptive controllers. (see for instance Ijspeert et al Science 2007, Ijspeert Science 2014, and Nyakatura et al Nature 2019). He is also investigating how to assist people with limited mobility using exoskeletons and assistive furniture. He is regularly invited to give talks on these topics (e.g. TED talk given at TED Global Geneva, Dec 8 2015). With his colleagues, he has received paper awards at ICRA2002, CLAWAR2005, IEEE Humanoids 2007, IEEE ROMAN 2014, CLAWAR 2015, SAB2018, and CLAWAR 2019. He is an IEEE Fellow, member of the Board of Reviewing Editors of Science magazine, and associate editor for the IEEE Transactions on Medical Robotics and Bionics and for the International Journal of Humanoid Robotics. He has acted as an associate editor for the IEEE Transactions on Robotics (2009-2013) and for Soft Robotics (2018-2021). He was a guest editor for the Proceedings of IEEE, IEEE Transactions on Biomedical Engineering, Autonomous Robots, IEEE Robotics and Automation Magazine, and Biological Cybernetics. He has been the organizer of 7 international conferences (BioADIT2004, SAB2004, AMAM2005, BioADIT2006, LATSIS2006, SSRR2016, AMAM2019), and a program committee member of over 50 conferences.

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BIOENG-404: Analysis and modelling of locomotion

The lecture presents an overview of the state of the art in the analysis and modeling of human locomotion and the underlying motor circuits. Multiple aspects are considered including neurophysiology, gait characterization, biomechanics, numerical modeling, neuroprosthetics, and links to biped robots

CS-432: Computational motor control

The course gives (1) a review of different types of numerical models of control of locomotion and movement in animals, (2) a presentation of different techniques for designing models, and (3) an analysis of the use and testing of those models in robotics and neuroprosthetics.

ENG-615: Topics in Autonomous Robotics

Students will be introduced to modern approaches in control and design of autonomous robots through lectures and exercises.

Robot

A robot is a machine—especially one programmable by a computer—capable of carrying out a complex series of actions automatically. A robot can be guided by an external control device, or the contro

Robotics

Robotics is an interdisciplinary branch of electronics and communication, computer science and engineering. Robotics involves the design, construction, operation, and use of robots. The goal of rob

Animal locomotion

Animal locomotion, in ethology, is any of a variety of methods that animals use to move from one place to another. Some modes of locomotion are (initially) self-propelled, e.g., running, swimming, ju

A New Methodological Approach to Analyze Human Roles in Human-Robot Interaction Scenarios

Auke Ijspeert

The influence of robotics in the job market has socio-economic consequences and the inevitable loss of job positions, but in the Human-Robot Interaction (HRI) scenarios, where humans and robots work together, new jobs and business models will be created. These HRI scenarios can be seen in manufacturing, medicine, maintenance, education, etc. and in the future, in most of the daily tasks. The purpose of this article is to analyze from the perspective of Human-Robot Interaction scenarios, which new HRI human roles and HRI tasks categories has to be taken into account. The new HRI human roles will serve to define and homogenize the transverse skills needed for workers working in HRI scenarios and for analyzing the human roles in HRI experiments. We introduce a methodological approach using the TERRINet HRI Template, which facilitates the analysis of tasks that in the near future will be done by humans working with robots. The Template has been used and tested in 20 study cases of HRI scenarios, validating the methodology and looking for homogenization in human roles.

IEEE2022

CPG-RL: Learning Central Pattern Generators for Quadruped Locomotion

Guillaume Denis Antoine Bellegarda, Auke Ijspeert

In this letter, we present a method for integrating central pattern generators (CPGs), i.e. systems of coupled oscillators, into the deep reinforcement learning (DRL) framework to produce robust and omnidirectional quadruped locomotion. The agent learns to directly modulate the intrinsic oscillator setpoints (amplitude and frequency) and coordinate rhythmic behavior among different oscillators. This approach also allows the use of DRL to explore questions related to neuroscience, namely the role of descending pathways, interoscillator couplings, and sensory feedback in gait generation. We train our policies in simulation and perform a sim-to-real transfer to the Unitree A1 quadruped, where we observe robust behavior to disturbances unseen during training, most notably to a dynamically added 13.75 kg load representing 115% of the nominal quadruped mass. We test several different observation spaces based on proprioceptive sensing and show that our framework is deployable with no domain randomization and very little feedback, where along with the oscillator states, it is possible to provide only contact booleans in the observation space.

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Gait-dependent Traversability Estimation on the k-rock2 Robot

Mohammadreza Ebrahimi, Matthew Alfonso Estrada, Auke Ijspeert

Assessing the traversability of rugged terrain is a difficult challenge for legged robots, especially when they implement multiple, distinct gaits. We tackle this problem on the k-rock2 amphibious, sprawling gait robot by training a gait-dependent traversability estimator. We verify that the estimator, trained solely on procedurally-generated simulated data, approaches the outcomes of real-world experiments conducted in an indoor motion capture arena using two distinct terrestrial gaits to cross various indoor obstacles. In simulation experiments on a large-scale outdoor heightmap representing real-world data, we quantify the performance gain using the estimator outputs for gait selection. Further, we apply the method to heightmaps of outdoor data to illustrate how the approach could readily he applied to field scenarios.

IEEE2022