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Autonomous Robots and Vehicles

Autonóm robotok és járművek
A tantárgyleírás hatályossága
Hatályosság kezdete:
2026. March 21.
Hatályosság vége:
Subject name (Hungarian, English)
Autonóm robotok és járművek
Autonomous Robots and Vehicles
Subject code BMEVIIIMA12
Subject type
Training Level
Course types and hours (weekly/semester)
Course type lecture tutorial laboratory
hours (weekly) 2 1 0
type (linked/independent) derived course
Assessment type vizsga
Credits 4
Subject coordinator
DR. Kiss Bálint
position: egyetemi docens
Responsible department
Irányítástechnika és Informatika Tanszék
Faculty Villamosmérnöki és Informatikai Kar
Subject website
Primary curriculum type
Direct prerequisites – Strong prerequisite none
Direct prerequisites – Weak prerequisite none
Direct prerequisites – Parallel prerequisite none
Direct prerequisites – Milestone prerequisite none
Direct prerequisites – Exclusion none

Objectives

Programme
1. Fundamentals in mechanics (1 week)
Controlled mechanism, trajectory, task, end effector. Levels of the control hierarchy, PTP and CP control, coordinated motion. Internal and external sensors. Unmanned aerial, ground and underwater vechicles.
  
2. Navigation methods of autonomous systems (2 weeks)
Orientation parameterization in navigation systems: elementary rotations, Rodriguez formula, Euler and RPY angles, homogeneous transformations. Navigation similarity of vehicles (car-like, aerial, marine). Sensors of navigation systems: differential GPS, 3D accelerometers, gyroscope, state estimation.
 
3. Dynamical models of mechanical systems (2 weeks)
Kinematic and potential energies, inertia tensors, Lagrange and Newton-Euler equations. Recursive an symbolical calculation of dynamical models.
 
 4. Geometric and kinematic models of robot arms (1 week)
Denavit-Hartenberg convention. Robot transformation graph. Direct and inverse geometry problems and their solutions. Differential motion, partial translational and rotational velocities, Jacobian matrix. Position, velocity and acceleration algorithms. Motion planning of redundant robot arms.
  
5. Control of robot arms (2 weeks)
Control of free motion: decentralized cascade joint level control, computed torque methods. Transformation of static forces and torques, Hybrid position and force control.
 
6. Robot programming languages and real-time implementation (1 week)
Architecture of robot programming languages: structured, task-based, model-based and cooperative languages, distributed systems. Path planning in joint space and in task space, realization of motion primitives. Real-time operating systems for control realization. 
 
7. Robot programming and robot controller systems (1 week)
Robot cell design, robot control software environments, robot simulation in virtual environments. Case studies
 
8. Motion planning and tracking control of mobile robots (2 weeks)
Kinematic model of mobile robots, reference robot, tracking control using state feedback techniques. Time optimal motion plnanning (Reeds-Sheepp, Dubbins, diferentially driven robots). Environment mapping, obstacle avoidance algorithms (potential fields, behavior based strategies).
 
9. Intelligent actuators and their application in automotive control (2 weeks)
Intelligent actuators on a car: suspension systems, steering systems, break systems, and their integrated control. Increasing intelligence for autonomous behavior.
The subject summarizes the theoretical and practical fundamentals of the modeling, control and intelligent architectural realization methods of robotic and autonomous systems. The subject provides concepts and system engineering background for maintenance and development engineers of such systems. Robotized manufacturing cells, widely used robot structures and the typical programming methodology of robotic arms are presented. Robot modeling, navigation and motion planning methods are studied. Special emphasis is put on the real-time control methods of robot arms and mobile platforms. Possibilities of the cooperation of wheeled and legged mobile robots are enumerated. Current control end navigation challenges are overviewed. Students successfully completed the course requirements will have an in-depth understanding of the modelling, real-time control and navigation solutions employed in robotics so that he or she can can creatively employ and complement them as necessary in the case industrial applications (e.g. automotive and robotics).

Learning outcomes

Ez a tantárgy a KKK rendeletben meghatározott, következő kompetenciák fejlesztését szolgálja:

Knowledge

No learning outcomes recorded.

Skills

No learning outcomes recorded.

Attitudes

No learning outcomes recorded.

Autonomy and responsibility

No learning outcomes recorded.

Oktatási módszertan

The subject has two contact hours of lectures and one contact hour of practice session each week. Practice session include the study of application examples, solution of numerical examples, and implementation of algorithms.

Tanulástámogató anyagok

Online források
Lantos-Kiss-Harmati: Autonomous robots and vehicles handouts (electronically); Lantos-Márton: Nonlinear Control of Vehicles and Robots (Springer, 2011); Somló-Lantos-Cat: Advanced robot control (Akadémiai Kiadó, 1997)

Recommended preliminary knowledge for completing the subject

Knowledge type competencies
(azon előzetes ismeretek összessége, amelyek megléte nem kötelező, de a tantárgy eredményes teljesítését nagyban elősegíti)
Mathematics, Physics, Informatics, Control engineering
Skill type competencies
(azon előzetes képességek és készségek összessége, amelyek megléte nem kötelező, de a tantárgy eredményes teljesítését nagyban elősegíti)
nincs
Recommended (non-compulsory) preliminary competencies
(azon ajánlott (nem kötelező) előzetesen megszerzendő kompetenciák összessége, amelyek jelentősen hozzájárulnak a tantárgy eredményes teljesítéséhez)
Mathematics, Physics, Informatics, Control engineering
General rules
Requirements: a. During the period of classes: successful midterm exam (at least pass grade). The result of the midterm exam count for the exam grade with up to 20%. Requirement for signature: the result of the midterm exam is at least 2 (pass). b. During the period of exams: no exam is possible without the signature. The exam is written composed of theoretical questions and exercises.  c. Early exam: not available Additional possibilities: The mid-term can be repeated once during the period of classes and once during the repeat period.
Assessment methods
In-term assessments

No detailed assessments provided.

Weight of in-term assessments

No weights provided.

Exam-period assessments

No detailed assessments provided.

Weight of exam elements

No weights provided.

Grade calculation

No grade thresholds provided.

Attendance requirements

No attendance requirements provided.

Rules for retake and resubmission

Not provided.

Short description

Not provided.

Detailed description

Not provided.

Recommended courses

Not provided.

Workload to complete the subject

No workload breakdown provided.

Validity of subject requirements
Requirements valid from:
Requirements valid until:
Curriculum placement

No curriculum placements recorded for this subject version.