Welcome to the 6th edition of the Workshop on Legged Robots.
This workshop was held at ICRA 2022 in May 27. The recorded talks can be found here.
Most of the environments surrounding us are rough, unstable, deformable and unstructured, which is dangerous and difficult for humans to access.
In these environments, legged robots have inherent advantages in locomotion over their wheeled or tracked counterparts.
The ability of legged robots to traverse different types of terrains and step over obstacles makes them uniquely suited to perform tasks in various scenarios.
These scenarios include search and rescue missions, inspection in complex and cluttered environments, planetary exploration, agriculture, etc.
Despite their capabilities, there still remain many challenges in making legged robots suitable for a widespread deployment in the real-world.
This workshop continues to investigate the technological ingredients that are missing for an effective widespread deployment of legged robots.
Invited speakers from industry and academia will be featured alongside their robots,
and papers highlighting problems and solutions in this domain will be solicited.
Topics of Interest:
Model Predictive Control (MPC)
Whole-Body Control (WBC)
Nonlinear Safety-Critical Control
Reinforcement Learning for Locomotion
Learning for Perception and Mapping
Learning Dynamics and Control
Robotic Systems Design
Novel Actuator Technologies
Perception & Mapping
SLAM in Static/Dynamic Environments
Robotic Assistive Devices
We do not support military applications and weapons systems for legged robots.
click on every speaker for the talk's title and abstract, and for the speaker's bio.
University of Oxford, UK
University of Oxford, UK
Agile Locomotion and Manipulation in Complex and Dynamic environments
The capabilities and agility of legged robots has evolved in leaps and bounds in recent years, with mobile robots now on the verge of becoming ubiquitous. In this talk, I will cover recent work by the Dynamic Robot Systems group at the University of Oxford in optimisation- and learning-based methods for locomotion, manipulation, and loco-manipulation. In particular, the talk will highlight recent advances in Model Predictive Control for achieving highly agile behaviours, how we can leverage generative models to uncover interpretable representations for locomotion control, and how we can make robotic systems operate more seamlessly in shared environments with people.
Wolfgang is a Robotics Research Associate at the Oxford Robotics Institute, University of Oxford focusing on optimal planning and control of high degree of freedom systems interacting with environments working with Dr. Ioannis Havoutis. He currently works in the context of the EU Horizon 2020 project Memory of Motion (MEMMO) and the Offshore Robotics for Certification of Assets Hub (ORCA).
He completed his PhD in Robotics and Autonomous Systems supervised by Prof. Sethu Vijayakumar at the University of Edinburgh, where he was a core member of the humanoids research group working on the Edinburgh-NASA Valkyrie project. Previously, he completed a MSc by Research (Distinction) in Robotics and Autonomous Systems and a BEng (Honours, 1st Class) in Mechanical Engineering with Management.
Italian Institute of Technology, Italy
Quadruped Design and Applications in Agriculture and Space Exploration
The Dynamic Legged Systems lab has been developing quadruped robots and
their locomotion control for over 15 years. In this talk, I will first
introduce important design upgrades of our 140kg hydraulic HyQReal
robot. Next, I will show the most recent results of our project VINUM
that focuses on the automation of winter pruning in vineyards with
quadruped robots. Last, my talk will take you into the field of space
exploration. I will present the current progress of our ESA-funded
project ANT that investigates the control and navigation aspects of
quadruped and hexapod robots during space exploration in hard-to-access
areas like craters.
Claudio Semini is the head of the Dynamic Legged Systems (DLS) lab at
Istituto Italiano di Tecnologia (IIT). He received an MSc degree from
ETH Zurich in 2005 and spent 2 years in Tokyo for his research at Tokyo
Tech and Toshiba. During his PhD (2010) and subsequent PostDoc at IIT,
he developed the quadruped robot HyQ. He has published more than 100
publications in international journals and conferences. He is/was the
coordinator/partner of several EU-, National and Industrial projects
(HyQ-REAL, INAIL Teleop, Moog@IIT joint lab, ESA-ANT, etc). His research
interests include the construction and control of heavy-duty legged
robots for application in real-world operations, legged locomotion,
Massachusetts Institute of Technology, USA
Dynamic Walking with Footstep Adaptation on the MIT Humanoid via Linear Model Predictive Control
This is a tandem talk between Prof. Kim and Dr. Ding.
Prof. Sangbae will present some of the recent work on locomotion for humanoid and quadruped robots,
and Dr. Ding will present his recent work on MPC for the MIT Humanoid robot.
Prof. Sangbae Kim, is the director of the Biomimetic Robotics Laboratory and a Professor of Mechanical Engineering at MIT. His research focuses on the bio-inspired robot design by extracting principles from animals. Kim's achievements on bio-inspired robot development include the world's first directional adhesive inspired from gecko lizards, and a climbing robot, Stickybot, that utilizes the directional adhesives to climb smooth surfaces featured in TIME's best inventions in 2006. Recent achievement includes the development of the MIT Cheetah capable of stable outdoor running up to 13mph and autonomous jumping over an obstacles at an efficiency of animals. This achievement was covered by more than 300 media articles. He is a recipient of best paper award from International Conference on Robotics and Automation (2007), King-Sun Fu Memorial Transactions on Robotics (2008) and IEEE/ASME transactions on mechatronics (2016), DARPA Young Faculty Award (2013), NSF CAREER award (2014), and Ruth and Joel Spira Award for Distinguished Teaching (2015).
Dr. Yanran Ding received his Ph.D. from the Mechanical Science and Engineering Department, University of Illinois at Urbana-Champaign (UIUC) in 2021. He is currently a post-doc at the biomimetic robotics lab at MIT working with Prof. Sangbae Kim. His research focuses on optimization-based control for both quadrupedal and humanoid robots to achieve dynamic motions. He is one of the best student paper finalists in the IROS 2017. His work on SO(3) MPC is recognized as the best paper finalist in the model-based optimization for Robotics Technical Committee, 2021.
ETH Zurich, Switzerland
ETH Zurich, Switzerland
Should I use MPC or RL?
Abstract: In this tandem talk between Ruben Grandia and Takahiro Miki, two experts in MPC and RL working on the same machine, we will present some of our very recent works in MPC and RL for legged locomotion. We will elaborate and discuss what works (and what not).
Bio: Marco Hutter is Professor for robotics at ETH and co-founder of ANYbotics AG. Ruben Grandia and Takahiro Miki are PhD students at the same lab. Our passion is to work on new approaches to make legged robots able to move across very challenging terrain. For more information, check out www.rsl.ethz.ch
University College London, UK
University College London, UK
Multi-Expert Learning of Adaptive Skills and Perceptual Locomotion
Abstract: This talk focuses on the recent advances in learning-based control for legged
locomotion, featuring multi-skill locomotion and perceptual locomotion. The talk will
briefly review the state of the art in legged locomotion first, primarily on the "deep
reinforcement learning" for continuous robot control in recent years.
Then I will elaborate on the ideas and principles of multi-expert architecture for
diversifying and fusing expert skills, and show how new locomotion skills perform in fall
recovery, trotting, target-following and any arbitrary transitions. Followed by a brief
introduction of how this architecture can be extended for manipulation. Then, I will
present the meta-learning approach, in which the robot can constantly updates the
interaction model and applies Model Predictive Control for generating the optimal
actions to maximize the reward. The meta-learning approach learns different latent
vectors of each condition and achieves online model adaptation within 0.2s, and the
SpotMicro robot can produce adaptive and robust locomotion under changing ground
friction, external pushes, and different robot dynamics including motor failures and the
whole leg amputation.
Lastly, we will take a look how perceptual locomotion can be achieved using only sparse
visual feedback from direct depth measurements and yet the Anymal robot can traverse
over a range of common terrains in human-centered environments (steps, ramps, gaps,
and stairs). The talk will be concluded with a short interactive open discussion about the
future directions and how researchers from different disciplines can collaborate and
explore new research areas.
Bio: Dr Zhibin (Alex) Li is an Associate Professor at the University College London and leads
the Advanced Robotics Intelligence Laboratory. His work in 2019-2020 - "multi-expert
learning of adaptive legged locomotion" - is the first implementation of a multi-expert
learning architecture for adaptive quadrupedal locomotion on a real robot (December
2020 issue, Science Robotics).
His research interest covers dynamic motion skills of locomotion and manipulation,
optimization-based motion planning and control, and deep reinforcement learning for
robot motor learning including locomotion, manipulation and grasping. He led the
theme of "Shared and Autonomous Manipulation" in joint cross-hub demonstration of
the UK National Robotics and Artificial Intelligence Hubs, and is working to develop
novel optimization and learning based robot control to achieve a new level of robot
autonomy and intelligence.
Boosting Teleoperation of Humanoids Robots with Machine Learning: Auto-Tuning, Anticipation and Resilience
Humanoid robots are versatile platforms that can be used to accomplish a variety of missions. We believe that they can be the most useful as avatars, i.e., deployed in remote and dangerous locations, teleoperated by a human. While high-level decisions and even gestures can be commanded by the human, the robot needs to be physically capable to execute a variety of tasks without prior planning, which requires generic whole-body controllers and resilience in face of potential damages, and to compensate for communication delays that may affect the performance of the teleoperation. In this talk, I will present our solutions to these problems, which is based on the use of machine learning techniques in combination with whole-body controllers. I will show several results obtained on the real robots iCub and Talos.
Serena Ivaldi is a tenured research scientist at Inria, leading the humanoid and human-robot interaction activities of the Team Larsen in Inria Nancy, France. She obtained her Ph.D. in Humanoid Technologies in 2011 at the Italian Institute of Technology. Prior to joining Inria, she was a post-doctoral researcher in UPMC in Paris, France, then at the University of Darmstadt, Germany. She has been PI of several collaborative projects, such as the EU projects CoDyCo (FP7), AnDy (H2020), EuRobin (HE), concerning the development of advanced anticipatory control and interaction skills for humanoid robots and exoskeletons.
She was Program Chair of the conference IEEE/RAS Humanoids 2019, co-leader of the Humanoid Robotics Group of GDR Robotique (the French Robotics society), and one of the judges of the Xprize ANA Avatar competition on telexistance and teleoperation of robots. She is also serving as Editor in Chief of the International Journal of Social Robotics and associate Vice-President of IEEE/RAS Member Activies Board. She was recently awarded the Suzanne Zivi Prize for excellence in research and she was nominated by Robohub and Women in Robotics in the list of “50 Women in Robotics you need to know about” in 2021.
University of Cape Town, ZA
University of Cape Town, South Africa
Studying Cheetahs to Build the Next-Generation of Robots
Maneuverability is paramount to survival for animals and will be equally important to legged
robots if they are to ever leave the safety of the laboratory. The cheetah (Acinonyx jubatus) is
the pinnacle of maneuverability and can rapidly accelerate and initiate turns at high-speed on
unpredictable terrain. However, biomechanics researchers are still far from understanding the
whole-body control of cheetah locomotion as conventional GPS/IMU collars cannot provide
the required data.
In this talk I will discuss my lab’s efforts towards the challenging problem of understanding the
locomotion of the cheetah. We do this through the lens of robotics and employ novel
techniques including multi-body modelling, feedback control, computer vision & deep learning,
physical robots, and trajectory optimization. These results are also relevant to the design of
future legged robotic systems which will perform time-critical tasks in unstructured world.
Amir Patel is an Associate Professor in the Departmental of Electrical Engineering at the University of
Cape Town (UCT) and the Director of the African Robotics Unit (ARU). He completed his undergraduate
degree in Mechatronics Engineering (2008) and MS in Electrical Engineering (2011) at UCT. Since 2012
he has been employed by UCT where he also completed his PhD in 2015. In 2018, he was appointed
as a Visiting Research Scholar at Carnegie Mellon University (Robomechanics Lab with Aaron Johnson)
and Johns Hopkins University (LIMBS Lab with Noah Cowan).
His primary research focus is to understand maneuverability in Africa’s fastest animals with a view to
building more agile robotic systems. He does this through the lens of a roboticist using techniques
such as trajectory optimization, state estimation, feedback control and bio-inspired robotic
experiments. He has been the recipient of awards including the Claude Leon Emerging Researcher
Award (2012), the Oppenheimer Memorial Trust Fellowship (2017, 2022), the Future Leaders – African
Independent Research (FLAIR) Fellowship (2021) and the Google Research Scholar Award (2021).
Boston Dynamics, USA
Boston Dynamics, USA
Making Atlas Dance, Run, and Jump
Abstract: The Boston Dynamics Atlas humanoid robot can run, jump, flip, and dance using its 28 hydraulically-actuated joints. In this talk, I will discuss how we design behaviors for Atlas using trajectory optimization and animation, how we map those plans onto the world using perception, and how we execute those behaviors using nonlinear model-predictive control. I will also show how our recent developments in model-predictive control have improved whole-body coordination and performance for Atlas.
Bio: Robin Deits has been excited about walking robots since his first Lego Mindstorms kit. He spent his PhD years in the Robot Locomotion Group at MIT, where he worked on footstep planning and whole-body control during the DARPA Robotics Challenge. He is now a principal engineer at Boston Dynamics, where he works on behavior development and control for the latest generation of Atlas humanoid robots.
Agility Robotics, USA
Agility Robotics, USA
Bio: Jonathan W. Hurst is a Professor of Robotics, co-founder of the Oregon State University Robotics Institute, and Chief Technology Officer and co-founder of Agility Robotics. He holds a B.S. in mechanical engineering and an M.S. and Ph.D. in robotics, all from Carnegie Mellon University. His university research focuses on understanding the fundamental science and engineering best practices for legged locomotion. Investigations range from numerical studies and analysis of animal data, to simulation studies of theoretical models, to designing, constructing, and experimenting with legged robots for walking and running, and more recently, using machine learning techniques merged with more traditional control to enable highly dynamic gaits. Agility Robotics is extending this research to commercial applications for robotic legged mobility, working towards a day when robots can go where people go, generate greater productivity across the economy, and improve quality of life for all.
Building Robots for the Unstructured World
For decades the most useful robots have been found in highly structured spaces, following predetermined paths with sub-millimeter precision and on-off end effector activation. Recent advances in robotics is beginning to change this paradigm, offering potential for robots to be applied in far less structured settings including in operation around humans. The value of potential uses for such a robot are vast if the technological hurdles to create them can be overcome. In this talk we will discuss Apptronik's systems approach and progress in creating robots for the unstructured world that we live and work in every day.
Dr. Paine received his B.S., MS., and PhD. in the field of electrical engineering from the University of Texas at Austin. His research focused on high performance force-controlled robotic actuation technologies for unstructured applications. His academic contributions have seen adoption in over 1,000 peer reviewed citations, and numerous recreations all over the world. His academic accomplishments led to him being invited to collaborate on several high-profile robotics projects such as the Valkyrie Humanoid Robot at NASA-JSC, and robots developed by Meka Robotics. After graduating, he founded Apptronik to continue developing advanced robotic technology and to apply these technologies to commercial products. He currently serves as CTO and has led numerous robotics projects in the fields of exoskeletons, manipulators, and humanoids.
Unitree Robotics, China
Unitree Robotics, China
Accelerate the Global Marketization of High-Performance Quadruped Robots
Introduce some of the things that Unitree Robotics has done in the past year to promote the development of the high-performance quadruped robot industry.
Including technology, products and so on. And introduce some of the valuable things we are doing right now.
Wang Xingxing is the founder, CEO&CTO of Unitree Robotics.
During his master's degree (year 2013 to 2016), he independently completed the high-performance low-cost quadruped robot XDog, which is driven by the outer rotor brushless motor.
Established Unitree Robotics at the end of 2016, continued to promote the global marketization of high-performance low-cost quadruped robots.
Unitree Robotics has successively launched LaikaGo, AlienGo, A1, Go1 and B1 quadruped robot, along with Z1 dexterous robotic arm, he had led the development of the above, which are widely recognized by the market.
DARPA SubTerrain Challenge
University of Nevada, Reno
ETH Zurich, Switzerland
University of California, Berkeley
Sierra Nevada Corporation
Oxford Robotics Institute, United Kingdom
Norwegian University for Science and Technology (NTNU), Norway
Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia
Georgia Institute of Technology, USA
University of Colorado, Boulder
University of Colorado, Denver
Scientific Systems Company, Inc.
University of California, Santa Cruz
Accelerating Advances in Robotics through the DARPA Subterranean Challenge
Complex real-world environments continue to present significant challenges for fielding robotic teams, which often face expansive spatial scales, difficult and dynamic terrain, degraded environmental conditions, and severe communication constraints. Breakthrough technologies call for integrated solutions across autonomy, perception, networking, mobility, and human teaming thrusts. As such, the DARPA Subterranean Challenge sought novel approaches and new insights for discovering and demonstrating these innovative technologies, to help close critical gaps for robotic operations in complex and challenging underground environments.
Dr. Timothy Chung recently joined Microsoft and is leading a new strategic initiative focused on advanced autonomy and applied robotics, doing so within the Strategic Missions and Technologies division, which focuses on next-generation technology solutions for government and commercial applications. Prior to joining Microsoft, Dr. Chung served as a program manager at the Defense Advanced Research Projects Agency (DARPA) Tactical Technology Office, where he led the OFFensive Swarm-Enabled Tactics program and the DARPA Subterranean (SubT) Challenge. Previously, Dr. Chung served as an Assistant Professor at the Naval Postgraduate School and Director of the Advanced Robotic Systems Engineering Laboratory (ARSENL). Dr. Chung holds a Bachelor of Science in Mechanical and Aerospace Engineering from Cornell University. He also earned Master of Science and Doctor of Philosophy degrees in Mechanical Engineering from the California Institute of Technology.
ANYMAL with Wheels
CSIRO Data61, Australia
Poznan University of Technology, Poland
This workshop is supported by the IEEE RAS Technical Committees on
Mechanism and Design, and
Algorithms for Planning and Control of Robot Motion