Personal tools
You are here: Home SLMC Home Research videos

Research videos

Topology-based Representations for Motion Planning

We have developed methods to combine and exploit different representations for motion synthesis, with specific emphasis on generalization of motion to novel situations. We have demonstrated the benefits of our methods on problems where direct path finding in joint configuration space is extremely hard whereas local optimal control exploiting a representation with different topology can efficiently find optimal trajectories. Further, we have illustrated the successful online motion generalization to dynamic environments on challenging, real world problems.
Selected publications:

Vladimir Ivan, Dmitry Zarubin, Marc Toussaint, Taku Komura, Sethu Vijayakumar. Topology-based Representations for Motion Planning and Generalisation in Dynamic Environments with Interactions. IJRR (in press). 2013

Dmitry Zarubin, Vladimir Ivan, Marc Toussaint, Taku Komura and Sethu Vijayakumar. Heirachical Motion Planning in Topological Representations. Proc. Robotics: Science and Systems (R:SS 2012), Sydney, Australia (2012). [pdf]


BLUE: A Bipedal Robot with Variable Stiffness and Damping

We have designed a planar bipedal robot with joints capable of physically varying both their stiffness and damping independently – the first of its kind. Informed by human biophysics and locomotion studies, we designed an appropriate (heterogenous) impedance modulation mechanism that fits the necessary torque and stiffness range and rate requirements at each joint while ensuring the right form factor. In addition to hip, knee and ankle, the constructed robot is also equipped with a three part compliant foot modelled on human morphology.
Selected publications:

Alexander Enoch, Andrius Sutas, Shinichiro Nakaoka and Sethu Vijayakumar. BLUE: A Bipedal Robot with Variable Stiffness and Damping. Proc. 12th IEEE-RAS International Conference on Humanoid Robots, Osaka, Japan (2012). [pdf]


Optimal Variable Impedance Control in Dynamic Movement Tasks

We have developed techniques that can efficiently compute optimised spatiotemporal modulation of torque and impedance profiles for highly dynamic movements in compliantly actuated robots. The proposed methodology is applied to a ball throwing task where we demonstrate that: (i) the method is able to tailor impedance strategies to specific task objectives and system dynamics, (ii) the ability to vary stiffness leads to better performance in this class of movements, (iii) in systems with variable physical compliance, our methodology is able to exploit the energy storage capabilities of the actuators.
Selected publications:

David Braun, Florian Petit, Felix Huber, Sami Haddadin, Patrick van der Smagt, Alin Albu-Schäffer and Sethu Vijayakumar, Robots Driven by Compliant Actuators: Optimal Control under Actuation Constraints,IEEE Transactions on Robotics (IEEE T-RO), 29(5), pp. 1085-1101 (2013). [pdf]

David Braun, Matthew Howard and Sethu Vijayakumar, Optimal Variable Stiffness Control: Formulation and Application to Explosive Movement Tasks, Autonomous Robots, vol. 33, pp. 237-253 (2012) [pdf][DOI]

David Braun, Florian Petit, Felix Huber, Sami Haddadin, Patrick van der Smagt, Alin Albu-Schaeffer and Sethu Vijayakumar. Optimal Torque and Stiffness Control in Compliantly Actuated Robots. Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS 2012), Portugal (2012). [pdf]

David Braun, Matthew Howard and Sethu Vijayakumar. Exploiting Variable Stiffness in Explosive Movement Tasks. Proc. Robotics: Science and Systems (R:SS 2011), Los Angeles, CA, USA (2011). [pdf]
http://youtu.be/LSU_bdHdMXs

Matthew Howard, David Braun and Sethu Vijayakumar. Constraint-based Equilibrium and Stiffness Control of Variable Stiffness Actuators. Proc. IEEE International Conference on Robotics and Automation (ICRA 2011), Shanghai, China (2011). [pdf]

Andreea Radulescu, Matthew Howard, David Braun and Sethu Vijayakumar. Exploiting Variable Physical Damping in Rapid Movement Tasks. Proc. 2012 IEEE ASME International Conference on Advanced Intelligent Mechatronics, Taiwan (2012). [pdf]
AIM 2012 Best Student Paper Award Finalist
http://youtu.be/w4xg6mwoLlI


Spatio-temporal Optimization of Multi-phase Movements: Dealing with Contacts and Switching Dynamics

We address the optimal control problem of robotic systems with variable stiffness actuation (VSA) including switching dynamics and discontinuous state transitions. Our focus in this paper is to consider tasks that have multiple phases of movement, contacts and impacts with the environment. By modelling such tasks as an approximate hybrid dynamical system with time-based switching, we develop a systematic methodology to simultaneously optimize control commands, stiffness profiles and temporal aspect of the movement such as switching instances and total movement duration. Numerical evaluations on a simple switching system, a realistic brachiating robot model with VSA, and a hopper with variable stiffness springs demonstrate the effectiveness of the proposed approach.
Selected publications:

Jun Nakanishi and Sethu Vijayakumar. Exploiting Passive Dynamics with Variable Stiffness Actuation in Robot Brachiation. Proc. Robotics: Science and Systems (R:SS 2012), Sydney, Australia (2012). [pdf] [video]

Jun Nakanishi, Konrad Rawlik and Sethu Vijayakumar. Stiffness and Temporal Optimization in Periodic Movements: An Optimal Control Approach. Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS 2011), San Francisco (2011). [pdf]


Tactile Sensing: In Robots and Humans

Making sense of high dimensional tactile sensor data in robots and humans is an exciting challenge. We have developed a framework that uses active learning to help with sequential gathering of most informative data samples. We use information theoretic criteria to find the optimal actions to estimate parameters that affect the dynamics of objects—such as viscosity or internal degrees of freedom. We have also worked on information encoding in human tactile processing.
Selected publications:

Hannes Saal, Jo-Anne-Ting and Sethu Vijayakumar. Active Estimation of Object Dynamics Parameters with Tactile Sensors. Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS 2010), Taiwan (2010). [pdf]

Hannes Saal, Jo-Anne-Ting and Sethu Vijayakumar. Active sequential learning with tactile feedback. In: Teh YW and Titterington M (Eds.), Proc. 13th Int. Conf. on Artificial Intelligence and Statistics (AISTATS 2010), JMLR: W&CP 9:677-684, Chia Laguna, Sardinia, Italy (2010). [pdf]

Hannes Saal, Jo-Anne-Ting and Sethu Vijayakumar. Active Filtering for Robot Tactile Learning. In: Workshop on Adaptive Sensing, Active Learning, and Experimental Design, Neural Information Processing Systems (NIPS 2009), Whistler, Canada (2009). [pdf]

Hannes Saal, Sethu Vijayakumar and Roland Johansson. Information about Complex Fingertip Parameters in Individual Human Tactile Afferent neurons. The Journal of Neuroscience, 29(25):8022-8031, (2009). [pdf]

Hannes Saal, Sethu Vijayakumar and Roland Johansson. Information about present and past stimulus features in human tactile afferents. Proc. Computational and Systems Neuroscience COSYNE '08, Salt Lake City, Utah (2008). [poster]


iLIMB Vibrotactile Feedback

In collaboration with prosthesis developer Touch Bionics, we fit subjects with the i-limb, a state-of-the-art prosthetic hand, and an array of vibrating motors to communicate feedback from force and position sensors to the wearer. We have developed a novel manipulandum for understanding the sensorimotor processes involved in object grasping together with a closed-loop prosthetic hand, with 2 degrees of control and 32 channels of vibrotactile feedback of fingertip forces and finger positions.
Selected publications:

Ian Saunders and Sethu Vijayakumar. Continuous Evolution of Statistical Estimators for Optimal Decision-Making. PLoS ONE, vol. 7, No. 6 (2012) [pdf]

Ian Saunders and Sethu Vijayakumar. The Role of Feed-Forward and Feedback Processes for Closed-Loop Prosthesis Control. Journal of Neuroengineering and Rehabilitation (JNER), 8:60 (2011). [pdf]

Ian Saunders and Sethu Vijayakumar. A Closed Loop Prosthetic Hand as a Model Sensorimotor Circuit. Proc. ESF Intl. Workshop on Computational Principles of Sensorimotor Learning, Irsee, Germany (2009). [pdf]


Dimensionality Reduction to Exploit Constraints in Reinforcement Learning

We have developed methods to incorporate prior knowledge from demonstrations of individual robot postures into learning by extracting the inherent problem structure to find an efficient state representation. In particular, we used probabilistic, nonlinear dimensionality reduction to capture latent constraints present in the data. By learning policies in the extracted latent space, we were able to solve the planning problem in a reduced space that automatically satisfies task constraints.
Selected publications:

Sebastian Bitzer, Matthew Howard and Sethu Vijayakumar. Using Dimensionality Reduction to Exploit Constraints in Reinforcement Learning. Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS 2010), Taiwan (2010). [pdf]

Sebastian Bitzer, Stefan Klanke and Sethu Vijayakumar. Does Dimensionality Reduction improve the Quality of Motion Interpolation? Proc. 17th European Symposium on Artificial Neural Networks (ESANN ’09), Bruges, Belgium (2009). [pdf]

Sebastian Bitzer, Ioannis Havoutis and Sethu Vijayakumar. Synthesising Novel Movements through Latent Space Modulation of Scalable Control Policies. Asada et. al (eds.) Proc. Tenth International Conference on the Simulation of Adaptive Behavior (SAB '08), Springer-Verlag LNAI 5040, pp. 199-209, Osaka, Japan (2008). [pdf]


Learning Policies from Variable Constraint Data

We have developed a novel approach for learning (unconstrained) control policies from movement data, where observations come from movements under different constraints. We demonstrate our approach on systems of varying complexity, including kinematic data from the ASIMO humanoid robot with 27 degrees of freedom, and present results for learning from human demonstration.
Selected publications:

Matthew Howard, Stefan Klanke, Michael Gienger, Christian Goerick and Sethu Vijayakumar. Methods for Learning Control Policies from Variable Constraint Demonstrations. In: O. Sigaud and J. Peters (eds.): From Motor Learning to Interaction Learning in Robots, SCI 264, pp. 253-291, Springer-Verlag (2010). [pdf]

Matthew Howard, Stefan Klanke, Michael Gienger, Christian Goerick and Sethu Vijayakumar. A Novel Method for Learning Policies from Variable Constraint Data. Autonomous Robots, vol. 27, pp. 105-121 (2009). [pdf]

Chris Towell, Matthew Howard and Sethu Vijayakumar. Learning Nullspace Policies. Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS 2010), Taiwan (2010). [pdf]
http://youtu.be/dKfKK129tpk

Matthew Howard, Stefan Klanke, Michael Gienger, Christian Goerick and Sethu Vijayakumar. A Novel Method for Learning Policies from Constrained Motion. Proc. IEEE International Conference on Robotics and Automation (ICRA '09), Kobe, Japan (2009). [pdf]


Behaviour Generation in Humanoids

We have developed a method for learning potential based policies from constrained motion data. In contrast to previous approaches to direct policy learning, our method can combine observations from a variety of contexts where different constraints are in force, to learn the underlying unconstrained policy in form of its potential function.
Selected publications:

Matthew Howard, Stefan Klanke, Michael Gienger, Christian Goerick and Sethu Vijayakumar. Behaviour Generation in Humanoids by Learning Potential-based Policies from Constrained Motion. Applied Bionics and Biomechanics, Vol. 5, No. 4, pp.195-211, Taylor and Francis (2008). [pdf]

Matthew Howard, Stefan Klanke, Michael Gienger, Christian Goerick and Sethu Vijayakumar. Learning Potential-based Policies from Constrained Motion. Proc. 8th IEEE-RAS International Conference on Humanoid Robots (Humanoids), Dejong, Korea (2008) [pdf]


Outreach

BBC Bang Goes the Theory in our lab! Research profiles: Sethu Vijayakumar


Asimo in Edinburgh: The Making of the Show Asimo in Edinburgh: The Movie Of The Show


Inaugural lecture: Prof Sethu Vijayakumar Robots: The Future of Man or "Man of The Future"


Document Actions