Tutorial at IJCAI-16

Saturday July 9th. 8:45 - 12:45, Room 4

Optimality in Robot Motion and Action

Jean-Paul Laumond, Nicolas Mansard, LAAS-CNRS, Toulouse France

For robots and living beings, the link between actions expressed in the physical space and motions originated in the motor space, turns to geometry in general and, in particular, to linear algebra. In life science the application of optimality principles in sensorimotor control unravels empirical observations. The idea to express robot actions as motions to be optimized has been developed in robotics since the 1970s.

Most of the time, robot algorithms aimed at computing an optimal motion provide an optimized motion, which is not optimal at all, but is the output of a given optimization method. The distinction between optimized and optimal motion is first illustrated by a series of open problems in mobile robotics. Optimization is then introduced as motion selection principle in robot action with the support of many examples in humanoid robotics. Optimal motions are introduced action signatures. How to reveal what optimality criterion underlies a given action? The question opens challenging issues to inverse optimal control.

Tutorial Program:

1. What is optimal in robot motion planning and control?

2. What we know and what we do not know about optimal motion for wheeled mobile robots?

3. Optimization as selection principle: The stack of task approach

4. Motion as action signature

5. Inverse optimal control

Suggestion of readings

K. Mombaur, A. Truong, J.P. Laumond, From human to humanoid locomotion: an inverse optimal control approach. Autonomous Robots, Vol. 28, N. 3, 2010.

S. Hak, N. Mansard, O. Stasse, J.P. Laumond, Reverse Control for Humanoid Robot Task Recognition. IEEE Transactions on Systems, Man, and Cybernetics{Part B : Cybernetics, Vol. 42, N.6, 2012.

J.P. Laumond, N. Mansard, J.B. Lasserre, Optimality in Robot Motion : Optimal Versus Optimized Motion. Communications of the ACM, Vol. 57, N. 9, 2014.

J.P. Laumond, N. Mansard, J.B. Lasserre, Optimization as Motion Selection Principle in Robot Action. Communications of the ACM, Vol. 58, N. 5, 2015.

Organizers

Jean-Paul Laumond, IEEE Fellow, is a roboticist. He is Directeur de Recherche at LAAS-CNRS (team Gepetto) in Toulouse, France. He got his PhD in 1984. His research is devoted to robot motion. In the 90's, he has been the coordinator of two European Esprit projects PROMotion (Planning RObot Motion) and MOLOG (Motion for Logistics), both dedicated to robot motion planning and control. In the early 2000's he created and managed Kineo CAM, a spin-off company from LAAS-CNRS devoted to develop and market motion planning technology. Kineo CAM was awarded the French Research Ministery prize for innovation and enterprise in 2000 and the third IEEE-IFR prize for Innovation and Entrepreneurship in Robotics and Automation in 2005. Siemens acquired Kineo CAM in 2012. In 2006, he launched the research team Gepetto dedicated to Human Motion studies along three perspectives: artificial motion for humanoid robots, virtual motion for digital actors and mannequins, and natural motions of human beings. He teaches Robotics at Ecole Normale Supérieure in Paris. He has edited four books. He has published more than 150 papers in international journals and conferences in Robotics, Computer Science, Automatic Control and recently in Neurosciences. He has been the 2011-2012 recipient of the Chaire Innovation technologique Liliane Bettencourt at Collège de France in Paris. His current project Actanthrope (ERC-ADG 340050) is devoted to the computational foundations of anthropomorphic action.

LAAS-CNRS, 7 Avenue du Colonel Roche, 31077 Toulouse, France www.laas.fr/~jpl jpl@laas.fr +33 561336347

Nicolas Mansard is a permanent researcher at LAAS-CNRS, Toulouse since October 2008. He got his PhD at INRIA Rennes in 2006. He was a post-doc at AIST in Tsukuba in the French-Japanese JRL lab dedicated to humanoid robotics, and then a visiting researcher at the AI Lab of Stanford University. His research activities are concerned with sensor-based control, and more specifically the integration of sensor-based schemes into humanoid robot applications. It is an exciting research topic at the intersection of the fields of robotics, automatic control, signal processing and numerical mathematics. His main application field is currently the humanoid robotics, as it causes serious challenges that are representative of many other robot domains. Nicolas Mansard recently awarded the 2015 Bronze Medal by CNRS.

LAAS-CNRS, 7 Avenue du Colonel Roche, 31077 Toulouse, France www.laas.fr/~nmansard nmansard@laas.fr +33 561336830