# Juan Cortés presents Sampling-based algorithms for path-finding in continuous cost-spaces:

On 2018-03-06 10:00:00 at E112, Karlovo náměstí 13, Praha 2

Sampling-based algorithms for path-finding in continuous cost-spaces:

applications to robotics and structural biology

Summary:

In robotics, motion planning algorithms have traditionally aimed at finding

feasible, collision-free paths for a mobile system. However, beyond feasible

solutions, in many applications it is important to compute good-quality paths

with respect to a given cost criterion. When a cost function is defined on the

configuration space of the system, motion planning becomes a pathfinding

problem

in a continuous cost-space. The cost function associated with robot

configurations may be defined from the distance to obstacles in order to find

high-clearance solution paths. It may also be related to controllability, to

energy consumption, or to many other different criteria. In computational

structural biology, where robotics-inspirited algorithms are applied to

simulate

molecular motions, the cost function is usually

defined by the potential energy or the free energy of the molecular system.

Computing low energy paths in this context is important since they correspond

to

the most probable conformational transitions.

We have developed a variant of the popular RRT algorithm, called Transition-RRT

(T-RRT), to compute good-quality paths in high dimensional continuous

cost-spaces. The idea is to integrate a stochastic state-transition test,

similarly to the Metropolis Monte Carlo

method, which makes the exploration get focused on low-cost regions of the

space. The algorithm involves a self-tuning mechanism that controls the

difficulty of this transition test depending on the evolution of the

exploration

process, and which significantly contributes

to the overall performance of the method. T-RRT is a simple and general

algorithm that can take into account any type of continuous, smooth cost

function defined on the configuration space. It has been successfully applied

to

diverse robot path-planning problems as well as structural biology problems. We

have also developed several variants and improvements of the basic T-RRT

algorithm to solve more efficiently particular classes of problems, and to

guarantee (asymptotic) convergence to the optimal solution in an any-time

fashion.

Biography:

Juan Cortés received the engineering degree in control and robotics from the

Universidad de Zaragoza (Spain) in 2000. In 2003, he received the Ph.D. degree

in automated systems/robotics from the Institut National Polytechnique de

Toulouse (France). From 2004, he is CNRS researcher at LAAS (Toulouse, France).

His research interest is focused on the development of algorithms for computing

and analyzing the motion of complex systems. Applications of these algorithms

go

beyond robotics. Indeed, he is strongly involved in interdisciplinary research

in the areas of structural biology, biotechnology and materials science. Juan

Cortés has participated in numerous European and French national projects in

all these areas. Between 2009 and 2015, he was co-chair of the IEEE-RAS TC on

Algorithms for Planning and Control of Robot Motion. He has participated in the

organization of several international workshops, and he coordinates the winter

schools Algorithms in Structural Bioinformatics (AlgoSB) since 2012.

applications to robotics and structural biology

Summary:

In robotics, motion planning algorithms have traditionally aimed at finding

feasible, collision-free paths for a mobile system. However, beyond feasible

solutions, in many applications it is important to compute good-quality paths

with respect to a given cost criterion. When a cost function is defined on the

configuration space of the system, motion planning becomes a pathfinding

problem

in a continuous cost-space. The cost function associated with robot

configurations may be defined from the distance to obstacles in order to find

high-clearance solution paths. It may also be related to controllability, to

energy consumption, or to many other different criteria. In computational

structural biology, where robotics-inspirited algorithms are applied to

simulate

molecular motions, the cost function is usually

defined by the potential energy or the free energy of the molecular system.

Computing low energy paths in this context is important since they correspond

to

the most probable conformational transitions.

We have developed a variant of the popular RRT algorithm, called Transition-RRT

(T-RRT), to compute good-quality paths in high dimensional continuous

cost-spaces. The idea is to integrate a stochastic state-transition test,

similarly to the Metropolis Monte Carlo

method, which makes the exploration get focused on low-cost regions of the

space. The algorithm involves a self-tuning mechanism that controls the

difficulty of this transition test depending on the evolution of the

exploration

process, and which significantly contributes

to the overall performance of the method. T-RRT is a simple and general

algorithm that can take into account any type of continuous, smooth cost

function defined on the configuration space. It has been successfully applied

to

diverse robot path-planning problems as well as structural biology problems. We

have also developed several variants and improvements of the basic T-RRT

algorithm to solve more efficiently particular classes of problems, and to

guarantee (asymptotic) convergence to the optimal solution in an any-time

fashion.

Biography:

Juan Cortés received the engineering degree in control and robotics from the

Universidad de Zaragoza (Spain) in 2000. In 2003, he received the Ph.D. degree

in automated systems/robotics from the Institut National Polytechnique de

Toulouse (France). From 2004, he is CNRS researcher at LAAS (Toulouse, France).

His research interest is focused on the development of algorithms for computing

and analyzing the motion of complex systems. Applications of these algorithms

go

beyond robotics. Indeed, he is strongly involved in interdisciplinary research

in the areas of structural biology, biotechnology and materials science. Juan

Cortés has participated in numerous European and French national projects in

all these areas. Between 2009 and 2015, he was co-chair of the IEEE-RAS TC on

Algorithms for Planning and Control of Robot Motion. He has participated in the

organization of several international workshops, and he coordinates the winter

schools Algorithms in Structural Bioinformatics (AlgoSB) since 2012.