Princeton University

School of Engineering and Applied Science

Department of Mechanical and Aerospace Engineering

*Robotics and Intelligent Systems* provides students with a working knowledge of methods for design and analysis of robotic and intelligent systems. Particular attention is given to modeling dynamic systems, measuring and controlling their behavior, and making decisions about future courses of action. The content is necessarily broad, and the course level is introductory. The intent is to motivate and prepare students to conduct research projects and for further study through advanced courses in related areas.

**System Modeling**- Biological and Cognitive Paradigms for Robot Design
- Declarative-Procedural-Reflexive Hierarchy for Decision-Making and Control
- Articulated Robots
- Joint-Link (Denavit-Hartenberg) Transformations
- Mobile Ground Robots
- Uninhabited Air Vehicles
- Intelligent Agents

**Control System Principles**- Open- and Closed-Loop Control
- Time-domain and Frequency-domain Analysis
- Optimality and Constraints
- Stability and Performance
- Adaptation
- Control Actuation
- Closed-form and Probabilistic Path Planning

**Computing, Measurement, State, and Parameter Estimation**- Sensors and Sensing
- Formal and Fuzzy Logic
- Turing Machines and Concepts of Machine Learning
- Analog and Digital Systems
- Probability and Error Models
- Sensor-Based Estimation
- Extended Kalman and Particle Filters
- Simultaneous Location and Mapping (SLAM)

**Decision-Making and Machine Learning**- Decision Trees
- Bayesian Belief Networks
- Classification of Data Sets
- Task Planning for Individual and Multiple Agents

**Numerical Methods for Evaluation and Search**- Monte Carlo Simulation
- Genetic Algorithms
- Simulated Annealing
- Particle Swarm Optimization

**Expert Systems**- Production Systems
- Forward Chaining
- Backward Chaining

**Neural Networks for Classification and Control**- Training and Implementation of Network Architectures
- Feed-Forward Networks
- Associative Networks
- Cerebellar Model Articulation Controller
- Deep-Learning Algorithms

**Week 1**- Overview and Preliminaries

**Week 2**- Mobile Robots, Position, and Orientation
- Translational and Rotational Dynamics

**Week 3**- Flying and Swimming Robots
- Articulated Robots

**Week 4**- Transformation, Path Planning, and Trajectories
- Time Response of Dynamic Systems

**Week 5**- Dynamic Effects of Feedback Control
- Control Systems

**Week 6**- Sensors and Actuators
- Introduction to Optimization

**Week 7**- Numerical Optimization
- Dynamic Optimal Control

**Week 8**- Formal Logic, Algorithms, and Incompleteness
- Computers, Computing, and Sets

**Week 9**- Probability and Statistics
- Machine Learning

**Week 10**- Introduction to Neural Networks

**Week 11**- Neural Networks
- Information, Search, and Expert Systems

**Week 12**- State Estimation
- Stochastic Control

**Week 13**- Parameter Estimation and Adaptive Control
- Task Planning and Multi-Agent Systems

### Lecture Slides and Assignments

*Robotics and Intelligent Systems: A Virtual Reference Book*## Examples of Previous Term Paper Topics

- Ebots: Application of an Unguided Evolutionary Neural Network to Control Virtual Evolving Robots
- Use of Neural Networks to Distinguish Between Notes Played by Different Musical Instruments
- Using Markov Decision Processes to Decentralize Earthquake Relief Response in Afghanistan
- Evaluation of Neural Networks' Ability to Generalize in Pattern Recognition
- Federal Land Management Expert System
- Analysis of the US Postal Service as an Intelligent System
- Design of a Neural Network for Classification of News Articles
- Dynamic Modeling and Simulation of Flocking Behavior for Sandhill Cranes and Tufted Ducks
- Java Simulation of Autonomous Vehicles
- Hardware/Software Implementation of Laser-Pointer Control Using Head Motion
- Control of an Inverted Pendulum Using a Puma-Style Robot
- Design and Simulation of an Automated Mailman
- Use of a Modified Game of Life for Basic Image Enhancement
- Robotic Thermo-Probe for Sub-Surface Exploration of Europa
- Genetics-Based Learning System for Playing Poker
- Neural Network Design for Automated Spectral Calibration
- Neural Network for Scheduling Lateral Control Gains of a Large Jet Transport
- Neural Networks for Footstep Recognition
- Navigation Through a Randomly Generated Maze
- Path Following of a Nonholonomic Wheeled Mobile Robot
- Obstacle Avoidance Algorithms in Hovercraft Maneuvering Situations
- A Semi-Autonomous Robotic Camera for Filming Sporting Events
- Intelligent System for Attack Analysis and Defensive Deployment
- Predicting Student Course Evaluations with Neural Networks
- Genetic Algorithm for Course Scheduling
- Use of a Neural Network to Schedule Linear-Quadratic Control Gains for a Nonlinear Mixing Tank
- Simulation of an Evolutionary Baseball League
- A Robotic Baseball Pitcher
- Application of Neural Networks to EEG for Alertness Prediction
- Stock Market Prediction with Neural Networks
- Simulation of a Gliding Micro-Air Vehicle
- Trajectory Computation for an Autonomous Planetary Lander
- An Intelligent System for Emergency Medical Assessment
- Using a Neural Network Predictive Controller to Manage Type-1 Diabetes
- Control of an Autonomous Helicopter
- Genetic Strategy for Exploring the Martian Surface
- Cerebellar Model Articulation Control of a Solenoid Actuator
- Image Processing Using Neural Networks
- Vehicle Stability Control: Antilock Braking for Lateral Traction Control
- Use of Restricted Boltzmann Machines to Predict Retinal Ganglion Cell Response to White Noise Stimuli
- Using a Neural Network to Process Face Portraits to Determine Race and Sex
- An Intelligent System for Emergency Response
- State Estimation Methods For a Differential-Drive Robot
- Robust Motion Planning: Using Human-Robot Interaction to ensure success
- Simulation of 3D Obstacle Avoidance for an Autonomous Robotic Lamprey
- Design and Simulation of a System of Coordinated Soccer-Playing Mobile Robots
- Optimizing Team Movement in RoboCup
- Neural Networks for Image Compression
- Design and Simulation of a Dextrous Robotic Hand
- Neural Network Control of a Biped Walking Robot
- Neural Network for Robot Tracking and Control
- Visual Odometry Using SURF Feature Detection
- Neural Network to Play Five-in-a-Row
- Dynamic SAGA Animats
- SubSpace Methods for Image Recognition
- Genetic Algorithm and Neural Network to Solve an Extended Traveling Salesman ("Traveling Shopper") Problem
- Trading Stocks with a Radial Basis Function Network
- UAV Control and Collaboration
- Intelligent jamming of a wi-fi hotspot
- Neural Network to Classify Visual Data
- Intelligent Air Traffic Control
- Toggle Switch for Biological Neural Network
- Intelligent Music Selection Software
- Generating and Solving Mazes
- Autonomous Robotic Navigation
- Spherical Robot
- Maximally Efficient Scheduling
- Automated Pharmacies
- Neural Network to Classify Audio Signals
- Genetic Algorithm Music Composition
- Speaker Identification Using Neural Networks
- Music Chord Identification Using Simulated Natural Behavior
- Simulation of a Quadrotor Helicopter Navigating Through a Randomly Generated Maze
- Comparison of Neural Network Training with Genetic Algorithm Search Vowel Classification and Intelligent Auto-Harmonization
- A Simulation and Analysis of Single and Multiple Robot Mapping
- The Sand Flea: A Proposal and Simulation of an Intelligent Control System
- Design & Simulation of an Autonomous Airship
- Design and Simulation of a Self-Reconfiguring Modular Robot
- Simulation of the ATHLETE and its Control System in Blender Game Engine Alphabet Recognition
- Point Cloud Based Object Recognition Using Multilayer Neural Networks
- Integrated Intelligence System for Autonomous Commercial Drone Network
- Food Recognition using a Supervised Neural Network
- Neural Networks & Facial Recognition
- Robotics Testbed Implementation of Stabilized Coordinated Group Motion Patterns with Prescribed Relative Oscillatory Speed Phases for a System of Miabots
- Submersible Quadrotors
- Optimization of Turbine Efficiency with a Genetic Algorithm
- Optimization of a Path-following System using Genetic Algorithms
- Dancing Robots
- Kalman Filter for Quadcopter Tracking
- Bag of Features for Image Classification
- Genetically Optimized Neural Network Soccer
- Design and Synthesis of a Digital Neuron
- Trajectory Generation for Traffic Simulation using Genetic Algorithm, Random Forest, and Neural Networks
- Baxter, our Friend
- A.I. Art
- Genetic Algorithm Optimization for Control of an Autonomous Underwater Vehicle
- Analysis of the Mechanisms and Responses of the BB-8 Robotics System
- Neural Network Analysis of Dota 2 Drafting Phase
- Classification of Gene Data with Distortions
- Predicting Bitcoin Prices with Recurrent Neural Networks
- Extending A Game-theoretical Approach to Heterogeneous Multi-Robot Task Assignment
- Comparing Sampling Techniques for Learning Imbalanced Multiclass Datasets Using Deep CNNs
- Towards a Model of the Intuitive Surgical da Vinci System
- Python Simulation of a Path Planning Robot
- Computer Vision Assisted Drone Projectile Evasion
- Off-Road Vehicle Active Suspension Simulation
- Classifying Gender Based on Voice Using Computational Neural Networks
- Classification of Upper Limb Movements Using a Neural Network
- Methods for Robotic Navigation
- A Pattern-Learning System for Rammed-Earth Architecture Processes

## Selected Books

**Robotics**- H. Asada and J.-J. Slotine,
*Robot Analysis and Control*, J. Wiley & Sons, 1986. - C. Asfahl,
*Robots and Manufacturing Automation*, J. Wiley & Sons, 1992. - D. Auslander, J. Ridgely, and J. Ringgenberg,
*Control Software for Mechanical Systems*, Prentice-Hall, 2002. - G. Bekey,
*Autonomous Robots*, MIT Press, 2005. - M. Brady, J. Hollerbach, T. Johnson, T. Lozano-Perez, and M. Mason,
*Robot Motion: Planning and Control*, MIT Press, 1984. - H. Choset,
*Principles of Robot Motion*, MIT Press, 2005. - C. Close and D. Frederick,
*Modeling and Analysis of Dynamic Systems*, Houghton Mifflin, 1993. - P. Corke,
*Robotics, Vision, and Control*, Springer, 2011. - J. Craig,
*Introduction to Robotics Mechanics and Control*, Pearson, 2018. - R. Dorf,
*Robotics and Automated Manufacturing*, Reston (Prentice-Hall), 1983. - L. Joseph,
*Learning Robotics Using Python*, PACKT, 2015. - J. Jones and A. Flynn,
*Mobile Robots*, A. K. Peters, 1993. - G. Long,
*Fundamentals of Robot Mechanics*, Quintus-Hyperion, 2015. - P. McKerrow,
*Introduction to Robotics*, Addison-Wesley, 1991. - A. Mutambara,
*Mechatronics and Robotics: Design and Applications*, CRC Press, 1999. - Y. Nakamura,
*Advanced Robtics: Redundancy and Optimization*, Addison-Wesley, 1991. - U. Nehmzow,
*Mobile Robotics: A Practical Introduction*, Springer-Verlag, 2000. - S. Niku,
*Intoduction to Robotics*, Prentice Hall, 2011. - L. Nocks,
*The Robot*, Greenwood Technologies, 2007. - K. Ogata,
*System Dynamics*, Prentice-Hall, 1998. - B. A. Ogunnaike and W. H. Ray,
*Process Dynamics, Modeling, and Control*, Oxford University Press, 1994. - D. Rowell and D. Wormley,
*System Dynamics: An Introduction*, Prentice-Hall, 1997. - B.-Z. Sandler,
*Robotics: Designing the Mechanisms for Automated Machinery*, Prentice-Hall, 1991. - J. Shearer, B. Kulakowski, and J. Gardner,
*Dynamic Modeling and Control of Engineering Systems*, Prentice-Hall, 1997. - B. Siciliano and O. Khatib,
*Springer Handbook of Robotics*, Springer, 2008. - R. Siegwart,
*Introduction to Autonomous Robots*, MIT Press, 2011. - D. Smith,
*Introduction to Dynamic Systems Modeling for Design*, Prentice-Hall, 1994. - W. Snyder,
*Industrial Robots: Computer Interfacing and Control*, Prentice-Hall, 1985. - M. Spong and M. Vidyasagar,
*Robot Dynamics and Control*, J. Wiley & Sons, 1989. - A. Staugaard, Jr.,
*Robotics and AI: An Introduction to Applied Machine Intelligence*, Prentice-Hall, 1987. - R. Stengel,
*Optimal Control and Estimation*, Dover Publications, 1994. (originally published as STOCHASTIC OPTIMAL CONTROL; Theory and Application, J. Wiley & Sons, 1986.) - J. Warren,
*Arduino Robotics*, Apress, 2011. - W. Wolovich,
*Robotics: Basic Analysis and Design*, Holt, Rinehart, and Winston, 1987. - R. Woods and K. Lawrence,
*Modeling and Simulation of Dynamic Systems*, Prentice-Hall, 1997.

- H. Asada and J.-J. Slotine,

**Intelligent Systems**- Albus, J. I., and Meystel, A. M.,
*Engineering of Mind*, J. Wiley & Sons, 2001. - P. Antsaklis and K. Passino,
*An Introduction to Intelligent and Autonomous Control*, Kluwer, 1993. - R. Arkin,
*Behavior-Based Robotics*, Bradford, 1998. - P. Baldi and S. Brunak,
*Bioinformatics*, Bradford, 1998. - C. Bishop,
*Neural Networks for Pattern Recognition*, Oxford University Press, 1995. - R. Brooks,
*Cambrian Intelligence*, Bradford, 1999. - E. Charniak and D. McDermott,
*Introduction to Artificial Intelligence*, Addision-Wesley, 1985. - P. Cohen and E. Feigenbaum, ed.,
*The Handbook of Artificial Intelligence*, William Kaufmann, 1982. - J. Giarratano and G. Riley,
*Expert Systems : Principles and Programming*, PWS Publishing, 1994. - J. Gleick,
*The Information: A History, A Theory, A Flood*, Vintage Books, 2011. - D. Goldberg,
*Genetic Algorithms in Search, Optimization, and Machine Learning*, Addison-Wesley, 1989. - M. Gupta, L. Jin, and N. Homma,
*Static and Dynamic Neural Networks*, J. Wiley & Sons, 2003. - D. Hofstadter,
*Godel, Escher, Bach: An Eternal Golden Braid*, Vintage, 1980. - J. Holland,
*Adaptation in Natural and Artificial Systems*, MIT Press, 1994. - J. Holland,
*Hidden Order*, Addison-Wesley, 1995. - D. Hudson and M. Cohen,
*Neural Networks and Artificial Intelligence for Biomedical Engineering*, IEEE Press, 2000. - L. Jain and C. de Silva,
*Intelligent Adaptive Control: Industrial Applications*, CRC Press, 1999. - S. Jain, D. Osherson, J. Royer, and A. Sharma,
*Systems That Learn*, Bradford, 1999. - D. Kortenkamp, R. Bonasso, and R. Murphy, ed.,
*Artificial Intelligence and Mobile Robots*, AAAI Press, 1998. - C. Lau, ed.,
*Neural Networks: Theoretical Foundations and Analysis*, IEEE Press, 1992. - P. McCorduck,
*Machines Who Think*, W. H. Freeman, 1979. - M. Norgaard, O. Ravn, N. Poulsen, and L. Hansen,
*Neural Networks for Modelling and Control of Dynamic Systems*, Springer-Verlag, 2000. - J. Pearl,
*Probabilistic Reasoning: Networks of Plausible Inference*, Morgan Kaufmann, 1988. - R. Penrose,
*The Emperor's New Mind*, Penguin Books, 1989. - B. Ripley,
*Pattern Recognition and Neural Networks*, Cambridge University Press, 1996. - E. Sanchez-Sinencio and C. Lau, ed.,
*Artificial Neural Networks: Paradigms, Applications, and Hardware implementations*, IEEE Press, 1992. - H. Simon,
*Sciences of the Artificial*, MIT Press, 1996. - R. Stengel, "Toward Intelligent Flight Control,"
*IEEE Trans. Systems, Man, and Cybernetics*, Vol. 23, No. 6, Nov-Dec 1993, pp. 1699-1717. - R. Sutton and A. Barto,
*Reinforcement Learning*, Bradford, 1998. - S. Tanimoto,
*The Elements of Artificial Intelligence Using Common Lisp*, W. H. Freeman & Co., 1995. - J. Thompson,
*Empirical Model Building*, J. Wiley & Sons, 1989. - K. P. Valavanis and G. N. Saridis,
*Intelligent Robotic Systems: Theory, Design, and Applications*, Kluwer, 1992. - R. Veroff, ed.,
*Automated Reasoning and Its Applications*, MIT Press, 1997. - L.-X. Wang,
*A Course in Fuzzy Systems and Control*, Prentice-Hall, 1997. - S. Weiss and C. Kulikowski,
*Computer Systems That Learn*, Morgan Kaufmann, 1991. - D. A. White and D. A. Sofge,
*Handbook of Intelligent Control*, Van Nostrand Reinhold, 1992. - P. Winston and R. Brown,
*Artificial Intelligence: An MIT Perspective*, MIT Press, 1979.

- Albus, J. I., and Meystel, A. M.,

Robert F. Stengel is Professor Emeritus and former Associate Dean of Engineering and Applied Science at Princeton University. He is the author of

*Optimal Control and Estimation*(Dover, 1994) and*Flight Dynamics*([Princeton University Press, 1st edition (2004), 2nd edition (2022)]. He was principal designer of the Apollo Lunar Module manual attitude control logic.**http://www.stengel.mycpanel.princeton.edu/MAE345.html**

*key words: robotics, intelligent systems, control systems, robot vehicles, industrial robots, optimization, numerical methods, neural networks, expert systems, task planning, Monte Carlo evaluation*

Last updated January 6, 2022.

Copyright 2022 by Robert F. Stengel. All rights reserved.