The following are the general topics of my research (more details by clicking’em):

• 
  COGNITIVE ROBOTICS

• Decision Making
  • Reinforcement learning in Robotics. Application of RL to learn diverse robotic skills/tasks and as a component in intelligent robotic architectures.
  • Decision making for robots. Automated decision making for robots under uncertainty, with large-scale state spaces and with special attention to low power computational platforms.
• Knowledge Inference
  • Bayesian inference for detecting and solving robotic sensor anomalies. Novel sensory architectures endowed with probabilistic deduction capabilities for improving the robustness of mobile robot operations.
• Task Planning
  • Semantic task planning for robots. Seminal works on the inclusion of semantic knowledge in mobile robots.
  • Hierarchical task planning for robots. Use of multiple mathematical abstraction for reducing the computational cost of robot task planning.
• Knowledge representation
  • Bayesian representations of robotic sensory systems. Representation of robot sensory systems with dynamic Bayesian networks and multiple ontological axes.
  • Symbolic, multi-hierarchical representations of the environment for mobile robots. Implementation and learning of multiple hierarchies to optimize different robot operations at once.
  • Semantic representations of the environment for mobile robots. Leveraging our multi-hierarchical abstraction approach to include semantic knowledge into a symbolic representation of the environment.
  • Hybrid metrical-topological representations of the environment for mobile robots. Probabilistically sound integration of topological and metrical maps into a Bayesian filter for SLAM.

• 
  STATISTICAL INFERENCE

• Mobile robot localization and mapping. Large-scale SLAM for mobile robots through Bayesian filtering.
• Modeling and prediction of stochastic delays in networked telerobots. Marginal probabilistic modelling of stochastic delays in remotely controlled sensory systems and novel clock synchronization algorithms.
• Statistical inference applied to civil safety in diverse sectors. Bayesian filtering applied to safety for construction workers and other civil contexts.
• Experimental design in Engineering. Sound application of analysis of variance to diverse research works.

• 
  ROBOTIC SOFTWARE DEVELOPMENT

• Software Engineering . Application of software engineering methodologies to robotic software development.
• Software Architectures. Design of intelligent robot control architectures.

• 
  TEACHING INNOVATION

• Teaching Innovation in Engineering. Diverse contributions to education in Engineering in an University context.