Robotics Engineering Certificate Program
The main objective of these certificates is to provide practicing engineers, interested in enhancing their knowledge, designing, servicing and maintaining robotic systems, a deep understanding of various topics in robotics technologies and a strong awareness of the systems within which robotics systems are engineered.
Robotics and Artificial Intelligence are disruptive technologies that pervade many industries and applications. While they are displacing some traditional industries and workers, additional ones are created. More people are needed to design and operate the new systems, and even more to fix them, when they break.
Bradley’s Robotics Engineering Certificate gives a solid foundation in the fundamental disciplines of robotics engineering that will help you advance in your career and open up additional career paths in this fast-growing field. The certificate program covers four broad topics, each at two levels of basic and advanced. Each of the 8 modules will be offered to a cohort of participants, subject to sufficient participant interest. Each module is 16 hours and will be offered in two 2-hour sessions per week with each module lasting 4 weeks. The Cost of each module is $1500. The following modules are planned.
Module 1A Basic Robot Fundamentals
This module presents an introduction to robotics with hands-on robotics experiments. In module projects, students construct robots which are driven by a microcontroller, with each project reinforcing the basic principles developed in lectures. This module will also expose the students to some of the contemporary happenings in robotics, which includes current robot lab research and robotics applications in the automotive, medical, agricultural, mining and construction fields.
- Robot Fundamentals
- Robot Programming
- Lab #1: Pick and Place
- Lab #2: Robot (decision making, e,g, Tic-Tac-Toe)
- Components of robotic systems
- Lab #3: Robot Mobility using LEGO® Mindstorm
- Obstacle Detection
- Lab #4: Obstacle avoidance using LEGO® Mindstorm
- 3D Printing
- Lab #5: 3D printed Robotic Arm
Module 1B Advanced Robot Concepts
This module covers some general robotics topics at an advanced level with hands-on robotics experiments. In module projects, students construct robots which are driven by a microcontroller, with each project reinforcing the basic principles developed in lectures. This module will also expose the participants to some of the contemporary happenings in robotics, which includes current robot lab research and robotics applications in the automotive, medical, agricultural, mining and construction fields.
- Sensors/Sensing/Force object recognition
- Robot Kinematics
- Lab #6: Kinematics verification-adept robot
- Microcontrollers (use of ARDUINO® boards)
- Lab #7: Traffic light control using ARDUINO® boards
- Lab #8: Advanced experiment using ARDUINO® boards
- Introduction to artificial intelligence (AI)
- Lab #9: “Smart” project using ARDUINO® boards
- Lab #10: Robotic arm completion
Module 2A Basic Machine Vision
This module provides the key elements of the different sensors used in the robotic systems and computer vision. It covers how these sensors work and how they are utilized in robotic systems. Students will have sufficient knowledge to acquire and implement different sensors in the robotic systems.
- Sensor classification
- Inertial sensors
- Lidar, sensors, accelerometers, radar
- GPS: what are they how they work
- How to integrate these with a block diagram
- Feature extraction from lidar
Module2B Advanced Machine Vision
This module provides the advanced topics necessary for utilization of different sensors used in the robotic systems and computer vision.
- Programming background: C++ and Python
- Math and probability background
- Image characterization
- Linear processing
- Edge detection/image relaxation: restoration and feature extraction
- Parametric transforms
- Team project selection and evaluation
Module 3A Basic Wireless Communication Systems
This module provides some basic knowledge pertaining to wireless communication theory, systems, and standards.
- Data, signals, modulation, and information transmission
- Noise and distortion in wireless systems, antennas, propagation and channel characteristics, attenuation/fading, link budget, transmitter and receiver front-end architectures, components, and characteristics
- Multiple-access strategies - frequency (FDMA), time (TDMA) and code (CDMA)
- 802.11a (Wi Fi), 802.11p, 802.11e, bluetooth
- Wireless network security
Module 3B Advanced Wireless Communication Systems
This module provides more advanced topics in wireless communication, including how the knowledge acquired in this module can be utilized to understand and design robotic systems.
- Digital coding, coder/decoders (codecs)
- Introduction to cellular systems: evolution from 1G to 4G and beyond, functional descriptions, capabilities, comparisons
- 4G cellular services, goals for 4G, HSPA+, LTE and LTE-advanced strategies, voice over LTE
- Mobile internet, mobile IP, TCP issues, HTTP, and mobile Web
- NTCIP standards for V2V communication
- Selected wireless systems
Module 4A Basic Motion Planning
This module provides an in-depth treatment of path planning and motion in robotic systems. Common techniques and algorithmic procedures used for planning and decision-making are covered.
- Discrete planning: Feasible planning, optimal planning, search algorithms
- Geometric representations and transformations: rigid-body transformations, 3D rotations, kinematic chains, Denavit-Hartenberg parameters
- Configuration space, C-space obstacles
- Motion planning: metric spaces, measure, random sampling, probabilistic road maps (PRMs), randomized potential fields, cell decomposition
- Optimization and probability review, Bayesian classification
- Information spaces: Kalman filtering
Module 4B Advanced Motion Planning
This module provides more advanced topics in path planning and motion in robotic systems. Case studies include mobile manipulation platforms and multi-robot systems. The student evaluation will be done by tests, homework, and projects.
- Motion control: PID, inverse dynamics control, robust adaptive control
- Simultaneous localization and mapping (SLAM)
- Topological and metric map models, grid and landmark-based maps
- Planning under sensing uncertainty: robot localization, mapping, navigation, searching, visibility-based pursuit-evasion, manipulation with sensing uncertainty
- Path-constrained trajectory planning, gradient-based trajectory optimization, topology-based trajectory
- System theory and analytical techniques: stability, Lyapunov functions, controllability
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