Robot arm kinematics (forward and inverse kinematics); robot arm dynamics (equations of motion, equivalent formulations); planning of manipulator trajectories; range sensing (time-of-flight and triangulation systems, nown target size, optical flow), proximity sensing (optical, magnetic, capacitive, inductive, ultrasonic), tactile (touch) sensing, force and torque sensing, dead reckoning (odometry and inertial sensing); mobile robots (localization, mapping, path planning, navigation, obstacle avoidance, object classification); multi-sensor data fusion.
İlk dosyayı sen ekleyebilirsin — notlar, geçmiş finaller, çözümler, cheat-sheet, ne varsa. Drive linki / PDF / ZIP / fotoğraf, hepsi olur.
Şu an: mail at, ben düzenleyip yayına alayım. Form/upload UX yakında geliyor (Kimya tasarlıyor).
| Dönem | Course CPA | |
|---|---|---|
| 2023-2024 Fall | 2.55 | 1 sec · 16 öğr |
| 2022-2023 Fall | 2.17 | 1 sec · 38 öğr |
| 2021-2022 Fall | 2.37 | 1 sec · 13 öğr |
| 2020-2021 Spring | 2.58 | 1 sec · 16 öğr |
| 2018-2019 Fall | 1.78 | 1 sec · 56 öğr |
| 2017-2018 Fall | 1.95 | 1 sec · 46 öğr |
| 2016-2017 Fall | 2.47 | 1 sec · 38 öğr |
| 2015-2016 Fall | 2.51 | 1 sec · 36 öğr |
| 2014-2015 Fall | 2.47 | 1 sec · 18 öğr |
| 2012-2013 Fall | 1.20 | 1 sec · 20 öğr |
Aggregate course GPA — Bilkent STARS'tan public data. Hoca-bazlı per-section detayı için STARS evaluation report →. Öğrenci anket cevapları KVKK kapsamında defter'de tutulmaz.
To attend the midterm exam and get a grade >=32.
The use of Generative Artificial Intelligence (GenAI) tools such as ChatGPT, Gemini, or DeepSeek is strictly prohibited during in-class assessments, including the midterm exam, final exam, quiz, and survey & in-class presentation.
nomenclature, robot manipulators, kinematic chain, links, joints, actuators, degrees of freedom, overview of forward and inverse kinematics rigid body transformations, properties of matrix transformations, translational, rotational, and scaling transformations, composite transformations center of rotation, Euler angles, homogeneous coordinates and transformations, composite homogeneous transformation matrix Denavit-Hartenberg representation (links, joints, and their parameters), arm matrix kinematic chain examples, forward kinematics equations inverse manipulator kinematics: methods of solution (numerical, closed-form) examples to algebraic and geometric solutions, workspace (dexterous, reachable), 6-DOF manipulator solution velocity kinematics and the Jacobian, derivation of the Jacobian, linear and angular velocity Jacobians, singularities Midterm Exam robot arm dynamics, forward and inverse dynamics, equivalent formulations, Lagrange-Euler formulation, equations of motion Newton-Euler and Generalized d'Alambert formulations to robot arm dynamics, forward and backward recursive equations planning of manipulator trajectories in joint space and Cartesian space, knot points, cubic spline trajectories, trajectories with polynomial segments, bounded deviations method introduction to sensing, classification of sensors, time-of-flight range sensors (ultrasonic, laser-based ranging), triangulation systems, proximity sensing (inductive, capacitive, magnetic, ultrasonic, optical) dead-reckoning systems (odometry, potentiometers, optical encoders, inertial sensing: gyroscopes, accelerometers, tilt sensors), multi-sensor data fusion ECTS - Workload Table: Activities Number Hours Workload Project (including preparation and presentation if applicable) 2 12 24 Individual or group work 4 2 8 Homework 2 8 16 Preparation for Midterm exam 1 24 24 Preparation for Final exam 1 32 32 Final exam 1 2 2 Midterm exam 1 2 2 Course hours 14 3 42 Total Workload: 150 Total Workload / 30: 150 / 30 5 ECTS Credits of the Course: 5 Type of Course: Lecture Course Material: Written - Multimedia - PC Teaching Methods: Lecturing - Mini Projects - Analytical Homework - Problem Solving Sessions