Do you want to solve the main problems of movements and trajectories in robots? This Postgraduate certificate will give you the keys. Enroll now”

This Postgraduate certificate is aimed at Computer Science professionals who wish to acquire specialized and specific knowledge in the field of Robotics. For this purpose, you will have a specialized team of teachers, who will provide all their knowledge in this course, which will be taught entirely online.

A program focused on Robot Planning Algorithms, where the students will be introduced to the classical planning algorithms and then, with a theoretical-practical approach, they will be able to solve problems that affect the autonomy of robots in different environments. Motion planning will be a key part of this program, where the students will also be introduced to the collaborative work of a group of robots.

Definition of strategies to assign tasks, creation of algorithms to plan coordinated movements, machine learning techniques, all in an education that will allow the IT professionals to acquire advanced knowledge, which will boost their careers in a growing Robotics sector.

An excellent opportunity offered by TECH to professionals who wish to advance in their careers while acquiring advanced learning. For this purpose, it has a university program with no fixed schedules and multimedia content that can be accessed 24 hours a day. They only need a cell phone, a computer or laptop with an Internet connection to view the syllabus or download the content to be able to consult it whenever they want.

Combine your professional career with a quality university program. Enroll now"

This Postgraduate certificate in Robot Planning Algorithms contains the most complete and up-to-date program on the market. The most important features include:

• Case studies presented by experts in robotic engineering
• The graphic, schematic, and practical contents with which they are created, provide scientific and practical information on the disciplines that are essential for professional practice
• Practical exercises where self-assessment can be used to improve learning
• Its special emphasis on innovative methodologies 
• Theoretical lessons, questions to the expert, debate forums on controversial topics, and individual reflection assignments
• Content that is accessible from any fixed or portable device with an Internet connection

This Postgraduate certificate will allow you to delve into the algorithms responsible for coordination in multi-robot systems. Enroll now”

The program’s teaching staff includes professionals from the sector who contribute their work experience to this educational program, as well as renowned specialists from leading societies and prestigious universities.

The multimedia content, developed with the latest educational technology, will provide the professional with situated and contextual learning, i.e., a simulated environment that will provide immersive education programmed to learn in real situations.

This program is designed around Problem-Based Learning, whereby the professional must try to solve the different professional practice situations that arise during the educational year. For this purpose, students will be assisted by an innovative, interactive video system created by renowned and experienced experts.

Progress in the Robotics sector with a highly qualified and experienced teacher team in this area"

A 100% online training that will allow you to master the technique of robot control. Enroll now"

This Postgraduate certificate has a syllabus composed of multimedia teaching material (video summaries, specialized readings, and simulations of real cases) to which the IT professional will have full access from the first day. With this extensive content, the students will delve into the main trajectory problems in mobile robots, planning in high dimensional robots, robot coordination, planning by decision and reinforcement learning. The Relearning learning system applied by TECH in all its programs will favor a more natural and progressive learning process.

This Postgraduate certificate will allow you to plan High Dimensional Robotic Systems and to face real problems that you will have to solve”

Module 1. Planning Algorithms in Robots

1.1. Classical Planning Algorithms

1.1.1. Discrete Planning: State Space 
1.1.2. Planning Problems in Robotics. Robotic Systems Models
1.1.3. Classification of Planners

1.2. The Trajectory Planning Problem in Mobile Robots 

1.2.1. Forms of Environment Representation: Graphs
1.2.2. Search Algorithms in Graphs
1.2.3. Introduction of Costs in Networks
1.2.4. Search Algorithms in Heavy Networks
1.2.5. Algorithms with any Angle Approach

1.3. Planning in High Dimensional Robotic Systems

1.3.1. High Dimensionality Robotics Problems: Manipulators
1.3.2. Direct/Inverse Kinematic Model
1.3.3. Sampling Planning Algorithms PRM and RRT
1.3.4. Planning Under Dynamic Constraints

1.4. Optimal Sampling Planning

1.4.1. Problem of Sampling-Based Planners
1.4.2. RRT* Probabilistic Optimality Concept
1.4.3. Reconnection Step: Dynamic Constraints
1.4.4. CForest. Parallelizing Planning

1.5. Real Implementation of a Motion Planning System

1.5.1. Global Planning Problem. Dynamic Environments
1.5.2. Cycle of Action, Sensorization. Acquisition of Information from the Environment
1.5.3. Local and Global Planning

1.6. Coordination in Multi-Robot Systems I: Centralized System

1.6.1. Multirobot Coordination Problem 
1.6.2. Collision Detection and Resolution: Trajectory Modification with Genetic Algorithms
1.6.3. Other Bio-Inspired Algorithms: Particle Swarm and Fireworks
1.6.4. Collision Avoidance by Choice of Maneuver Algorithm

1.7. Coordination in Multi-Robot Systems II: Distributed Approaches I

1.7.1. Use of Complex Objective Functions
1.7.2. Pareto Front
1.7.3. Multi-Objective Evolutionary Algorithms

1.8. Coordination in Multirobot Systems III: Distributed Approaches II

1.8.1. Order 1 Planning Systems
1.8.2. ORCA Algorithm
1.8.3. Addition of Kinematic and Dynamic Constraints in ORCA

1.9. Decision Planning Theory

1.9.1. Decision Theory
1.9.2. Sequential Decision Systems
1.9.3. Sensors and Information Spaces
1.9.4. Planning for Uncertainty in Sensing and Actuation

1.10. Reinforcement Learning Planning Systems

1.10.1. Obtaining the Expected Reward of a System
1.10.2. Mean Reward Learning Techniques
1.10.3. Inverse Reinforcement Learning

Enroll now and access a university program that will allow you to take a step further into the Robotics industry”