254 citations · 390 across the 30 of their papers we have counts for
10 papers · 1 filter
Bayesian optimization for robust robotic grasping using a sensorized compliant hand
Juan G. Lechuz-Sierra, Ana Elvira H. Martin, Ashok M. Sundaram +2
One of the first tasks we learn as children is to grasp objects based on our tactile perception. Incorporating such skill in robots will enable multiple applications, such as incre…
Gen-Swarms: Adapting Deep Generative Models to Swarms of Drones
Carlos Plou, Pablo Pueyo, Ruben Martinez-Cantin +3
Gen-Swarms is an innovative method that leverages and combines the capabilities of deep generative models with reactive navigation algorithms to automate the creation of drone show…
Active Exploration in Bayesian Model-based Reinforcement Learning for Robot Manipulation
Carlos Plou, Ana C. Murillo, Ruben Martinez-Cantin
Efficiently tackling multiple tasks within complex environments, such as those found in robot manipulation, remains an ongoing challenge in robotics and an opportunity for data-dri…
Finding safe 3D robot grasps through efficient haptic exploration with unscented Bayesian optimization and collision penalty
Joao Castanheira, Pedro Vicente, Ruben Martinez-Cantin +2
Robust grasping is a major, and still unsolved, problem in robotics. Information about the 3D shape of an object can be obtained either from prior knowledge (e.g., accurate models…
Bayesian Optimization with Adaptive Kernels for Robot Control
Ruben Martinez-Cantin
Active policy search combines the trial-and-error methodology from policy search with Bayesian optimization to actively find the optimal policy. First, policy search is a type of r…
Gaussian Mixture Models for Affordance Learning using Bayesian Networks
Pedro Osório, Alexandre Bernardino, Ruben Martinez-Cantin +1
Affordances are fundamental descriptors of relationships between actions, objects and effects. They provide the means whereby a robot can predict effects, recognize actions, select…
Body Schema Acquisition through Active Learning
Ruben Martinez-Cantin, Manuel Lopes, Luis Montesano
We present an active learning algorithm for the problem of body schema learning, i.e. estimating a kinematic model of a serial robot. The learning process is done online using Recu…
Robust Fusion for Bayesian Semantic Mapping
David Morilla-Cabello, Lorenzo Mur-Labadia, Ruben Martinez-Cantin +1
The integration of semantic information in a map allows robots to understand better their environment and make high-level decisions. In the last few years, neural networks have sho…
Unscented Bayesian Optimization for Safe Robot Grasping
José Nogueira, Ruben Martinez-Cantin, Alexandre Bernardino +1
We address the robot grasp optimization problem of unknown objects considering uncertainty in the input space. Grasping unknown objects can be achieved by using a trial and error e…
BayesOpt: A Library for Bayesian optimization with Robotics Applications
Ruben Martinez-Cantin
The purpose of this paper is twofold. On one side, we present a general framework for Bayesian optimization and we compare it with some related fields in active learning and Bayesi…