Advanced Robotics

• Teachers
• Weekly hours
• Competences
• Objectives
• Contents
• Activities
• Teaching methodology
• Evaluation methodology
• Bibliography
• Previous capacities

Teachers

Person in charge

• Isiah Zaplana Agut ( )

Others

• Anais Garrell Zulueta ( )

Weekly hours

Competences

Transversal Competences

Transversals

• CT1 - Entrepreneurship and innovation. Know and understand the organization of a company and the sciences that govern its activity; Have the ability to understand labor standards and the relationships between planning, industrial and commercial strategies, quality and profit.
• CT2 - Sustainability and Social Commitment. To know and understand the complexity of economic and social phenomena typical of the welfare society; Be able to relate well-being to globalization and sustainability; Achieve skills to use in a balanced and compatible way the technique, the technology, the economy and the sustainability.
• CT3 - Efficient oral and written communication. Communicate in an oral and written way with other people about the results of learning, thinking and decision making; Participate in debates on topics of the specialty itself.
• CT5 - Solvent use of information resources. Manage the acquisition, structuring, analysis and visualization of data and information in the field of specialty and critically evaluate the results of such management.
• CT8 [Avaluable] - Gender perspective. An awareness and understanding of sexual and gender inequalities in society in relation to the field of the degree, and the incorporation of different needs and preferences due to sex and gender when designing solutions and solving problems.

Basic

• CB3 - That students have the ability to gather and interpret relevant data (usually within their area of ??study) to make judgments that include a reflection on relevant social, scientific or ethical issues.
• CB5 - That the students have developed those learning skills necessary to undertake later studies with a high degree of autonomy

Technical Competences

Especifics

• CE15 - To acquire, formalize and represent human knowledge in a computable form for solving problems through a computer system in any field of application, particularly those related to aspects of computing, perception and performance in intelligent environments or environments.
• CE17 - To develop and evaluate interactive systems and presentation of complex information and its application to solving human-computer and human-robot interaction design problems.
• CE24 - To ideate, design and build intelligent robotic systems to be applied in production and service environments, and that have to be capable of interacting with people. Also, to create collaborative and social intelligent robotic systems.
• CE25 - To ideate, design and integrate mobile robots with autonomous navigation capability, fleet formation and interaction with humans.
• CE26 - To design and apply techniques for processing and analyzing images and computer vision techniques in the area of artificial intelligence and robotics
• CE28 - To plan, ideate, deploy and direct projects, services and systems in the field of artificial intelligence, leading its implementation and continuous improvement and assessing its economic and social impact.

Generic Technical Competences

Generic

• CG3 - To define, evaluate and select hardware and software platforms for the development and execution of computer systems, services and applications in the field of artificial intelligence.
• CG4 - Reasoning, analyzing reality and designing algorithms and formulations that model it. To identify problems and construct valid algorithmic or mathematical solutions, eventually new, integrating the necessary multidisciplinary knowledge, evaluating different alternatives with a critical spirit, justifying the decisions taken, interpreting and synthesizing the results in the context of the application domain and establishing methodological generalizations based on specific applications.
• CG5 - Work in multidisciplinary teams and projects related to artificial intelligence and robotics, interacting fluently with engineers and professionals from other disciplines.
• CG6 - To identify opportunities for innovative applications of artificial intelligence and robotics in constantly evolving technological environments.
• CG7 - To interpret and apply current legislation, as well as specifications, regulations and standards in the field of artificial intelligence.
• CG8 - Perform an ethical exercise of the profession in all its facets, applying ethical criteria in the design of systems, algorithms, experiments, use of data, in accordance with the ethical systems recommended by national and international organizations, with special emphasis on security, robustness , privacy, transparency, traceability, prevention of bias (race, gender, religion, territory, etc.) and respect for human rights.
• CG9 - To face new challenges with a broad vision of the possibilities of a professional career in the field of Artificial Intelligence. Develop the activity applying quality criteria and continuous improvement, and act rigorously in professional development. Adapt to organizational or technological changes. Work in situations of lack of information and / or with time and / or resource restrictions.

Objectives

1. Learn to program robots and design robotic applications.
   Related competences: CE24, CE25, CE26, CG4, CG6, CG8, CG9, CT1, CT5, CB3, CB5, CE15, CE17,
2. Be able to make judgments that include a reflection on relevant social, scientific or ethical issues related to current robotics and its potential applications.
   Related competences: CE28, CG5, CG6, CG7, CG8, CT2, CT3, CT8,
3. Learn to coordinate actions between robots.
   Related competences: CG3, CG5, CG6, CT3, CT5, CE15, CE17,
4. Be able to merge different sources of information to obtain, formalize and represent the physical environment in a computable way for problem solving.
   Related competences: CE24, CE25, CG3, CG5, CG6, CG8, CT2, CT5, CB3, CB5, CE17,
5. Application of Computer Vision techniques to Robotic Systems
   Related competences: CE24, CE25, CE26, CG4, CG5, CG6, CT5, CE15,
6. Application of Artificial Intelligence techniques to Robotic Systems
   Related competences: CE24, CE26, CE28, CG4, CG5, CG9, CT3, CT5, CE15, CE17,
7. Creation of interaction systems between robots and humans
   Related competences: CE24, CE25, CE26, CE28, CG3, CG4, CG5, CG6, CG7, CG8, CG9, CT1, CT3, CT5, CT8, CE15, CE17,

Contents

1. Introduction
   The contents that were achieved in the previous subject Introduction to robotics will be reviewed.
2. Introduction to motion planning -- The configuration space.
   Trajectory planning versus movement planning. Forward and inverse kinematics. Geometric and topological definition of the configuration space of a robotic manipulator.
3. Potential fields-based solutions to the motion planning problem.
   Discretization of the configuration space of a manipulator robot. Repulsive and attractive potential fields. Functions without local minima: Navigation functions and harmonic functions.
4. Sampling-based solutions to the motion planning problem.
   Sampling type (random, Halton, SDK, etc.). Methods based on road maps, Probabilistic Road Maps (PRMs), and exploration trees, Randomly Exploring Rapid Trees (RRTs) and their application to movement planning problems. Improvements to standard planners (PRM with Gaussian sampling, RRT-CONNECT, RRT*).
5. Task planning.
   Motion planning taking into account the restrictions imposed by the tasks. Modelling tasks with directed graphs. STRIPS and PDDLs languages. Search and heuristics guided search algorithms. FF algorithm.
6. Cognitive robotics.
   Ontologies. Types of ontologies and reasoning from ontologies. Behaviour trees (BTs).
7. Kinematics of mobile robots.
   Differential kinematics, differential constraints imposed by wheels and the concept of holonomic and non-holonomic robots (review). Differential kinematics, relationship between the velocity of a robotic platform and the differential constraints imposed by a single wheel, forward and inverse differential kinematics for a specific wheeled mobile robot.
8. Mobile robots' dynamics.
   Dynamics of a mobile robot. Modeling the dynamics.
9. Perception of mobile robots.
   Types of sensors. Error propagation. Visual Servoing.
10. Location of mobile robots.
    Introduction to map-based location. Review of probability theory. Markov approach. Kalman filter approach. The problem of SLAM. SLAM-EKF, FastSLAM, GraphSlam.
11. Route planning for mobile robots.
    Introduction, representations, collision avoidance. Potential fields. Solved example. Graph construction, graph search. Concepts applied to mobile robotics.

Activities

Activity Evaluation act

Teaching methodology

Evaluation methodology

Bibliography

Basic:

• Principles of robot motion : theory, algorithms, and implementation - Choset, Howie M, MIT Press, 2005. ISBN: 9780262033275
  https://discovery.upc.edu/discovery/fulldisplay?docid=alma991002885219706711&context=L&vid=34CSUC_UPC:VU1
• Robotics : modelling, planning and control - Siciliano, Bruno, Springer, cop. 2010. ISBN: 978-1-84996-634-4
  https://discovery.upc.edu/discovery/fulldisplay?docid=alma991003961269706711&context=L&vid=34CSUC_UPC:VU1
• Introduction to autonomous mobile robots - Siegwart, Roland; Nourbakhsh, Illah Reza; Scaramuzza, Davide, MIT Press, 2011. ISBN: 9780262015356
  
• Introduction to AI robotics - Murphy, R.R, The MIT Press, 2019. ISBN: 9780262348157
  

Previous capacities