Cognitive Robotics

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Credits
4.5
Types
Elective
Requirements
This subject has not requirements, but it has got previous capacities
Department
URV;CS
Mail
1.To understand the main types of cognitive robots and their driving requirements (engineering operations, navigation, cooperation).
2.To understand advanced methods for creating highly capable cognitive robots.
3.To dive into the recent literature, and collectively synthesize, clearly explain and evaluate the state of the art in cognitive robotics.
4.To apply one or more core reasoning methods to create a simple agent that is driven by goals or rewards.

Teachers

Person in charge

  • Albert Oller Pujol ( )

Others

  • Meysam Madadi ( )

Weekly hours

Theory
1.8
Problems
0
Laboratory
0.9
Guided learning
0
Autonomous learning
4.8

Contents

  1. Planning and Acting in the World.
    Monitoring and Diagnosis
    Planning Missions
  2. Interacting with the world: state-awareness
    SLAM
    Cognitive Vision
    Navigation and Manipulation
    Human-Robot Interaction
  3. Fast, large-scale reasoning: planning for future
    Optimality and soft Constraints
    Incremental methods

Activities

Activity Evaluation act


Implementation of theoretical contents into simulated environments



Theory
27h
Problems
0h
Laboratory
6h
Guided learning
0h
Autonomous learning
36h

Teamwork with simulated robots



Theory
0h
Problems
0h
Laboratory
7.5h
Guided learning
0h
Autonomous learning
36h

Teaching methodology

1. To understand the main types of cognitive robots and their driving requirements (engineering operations, navigation, cooperation)
Methodology: case studies

2. To understand advanced methods for creating highly capable cognitive robots
Methodology: lectures and classroom slides, implement and compare 2 core methods with computer simulation

3. To dive into the recent literature, and collectively synthesize, clearly explain and evaluate the state of the art in cognitive robotics
Methodology: oral presentation

4.To apply one or more core reasoning methods to create a simple agent that is driven by goals or rewards
Methodology: code programming

Evaluation methodology

1. Oral presentation 20%
2. Reports of lab sessions 30%
3. Final project 50%

(*) There are no exams.

Previous capacities

Good programming skills (C, C++, Matlab)