Robotics Engineering
Undergraduate Courses
ME 4322. Modeling and Analysis of Mechatronic Systems
Cat I (offered at least 1x per Year).
This course introduces students to the modeling and analysis of mechatronic systems. Creation of dynamic models and analysis of model response using the bond graph modeling language are emphasized. Lecture topics include energy storage and dissipation elements, transducers, transformers, formulation of equations for dynamic systems, time response of linear systems, and system control through open and closed feedback loops. Computers are used extensively for system modeling, analysis, and control. Hands-on projects will include the reverse engineering and modeling of various physical systems. Physical models may sometimes also be built and tested.
RBE 1001. Introduction to Robotics
Cat I (offered at least 1x per Year).
Multidisciplinary introduction to robotics, involving concepts from the fields of electrical engineering, mechanical engineering and computer science. Topics covered include sensor performance and integration, electric and pneumatic actuators, power transmission, materials and static force analysis, controls and programmable embedded computer systems, system integration and robotic applications. Laboratory sessions consist of hands-on exercises and team projects where students design and build mobile robots. Undergraduate credit may not be earned for both this course and for ES 2201.
RBE 100X. PROGRAMMING FOR ROBOTICS
This course introduces students to the fundamental principles of programming as it applies to robotic applications. Topics include data structures, control flow, modularization, state machines, and event-based input/output. Students will be expected to implement, test, and debug programs and apply them to microcontrollers. Special focus will be given to writing efficient and reusable code. This course provides appropriate programming background for RBE 1001.
RBE 2001. Unified Robotics I: Mechanical Applications in Robotics
Cat I (offered at least 1x per Year).
This course focuses on mechanical concepts in the design, construction, and actuation of a robot. Topics include the effective conversion of electrical power to mechanical power, power transmission and control for locomotion and payload manipulation, and the application of kinematic principles for the design of planar manipulators. The course will present the physical operation and common robotic applications of different types of actuators, including solenoids, electrical motors, and pneumatic, hydraulic, and soft actuators. The course will address the design of mechanical systems for a robot to meet requirements including chassis strength, durability, reliability, and robustness. Laboratory sessions consist of hands-on exercises and team projects where students design and test mechanical systems for specific tasks.
RBE 2002. Unified Robotics II: Sensing and Perception in Robotics
Cat I (offered at least 1x per Year).
This course focuses on how robot control and decision processes are informed through sensors. The course covers the operation and integration of simple and complex sensors, including signal transduction, interface circuitry, and physical integration. Themes include how functionality guides sensor selection; how decision-making is affected by uncertainty, and how performance can be improved through signal conditioning, digital filtering, calibration, parameter selection, and sensor fusion. The course will address how sensor inputs can be used to generate representations of the environment, and how a robot uses information to achieve goals within its environment. Laboratory sessions consist of hands-on exercises and team projects where students specify and test a variety of sensors to accomplish specific tasks.
RBE 3001. Unified Robotics III: Manipulation
Cat I (offered at least 1x per Year).
This is the third of a four-course sequence introducing foundational theory and practice of Robotics Engineering. The focus of this course is on analysis & control of robotic arms, robotic manipulation, and integration of complex robotic systems, i.e., the coordinated motion of multiple actuators to execute complex manipulation tasks in the physical space. Concepts of transformations along with position and velocity kinematics will be presented, and fundamental concepts of trajectory planning, robot forces and dynamics, computer vision, and control will be introduced. Theoretical methods learned in the classroom will be applied during practical laboratory sessions, which will culminate in the construction and programming of a vision-guided, multi degree of freedom robotic manipulator.
RBE 3002. Unified Robotics IV: Navigation
Cat I (offered at least 1x per Year).
Fourth of a four-course sequence introducing foundational theory and practice of robotics engineering from the fields of computer science, electrical engineering and mechanical engineering. The focus of this course is navigation, position estimation and communications. Concepts of dead reckoning, landmark updates, inertial sensors, and radio location will be explored. Control systems as applied to navigation will be presented. Communication, remote control and remote sensing for mobile robots and tele-robotic systems will be introduced. Wireless communications including wireless networks and typical local and wide area networking protocols will be discussed. Considerations will be discussed regarding operation in difficult environments such as underwater, aerospace, hazardous, etc. Laboratory sessions will be directed towards the solution of an open-ended problem over the course of the entire term.
RBE 3100. Social Implications of Robotics
Cat I (offered at least 1x per Year).
This course introduces students to the social, moral, ethical, legal, and current or future philosophical issues within the context of robotic systems and related emerging technology. Students will be expected to contribute to classroom presentations, discussions and debates, and to complete a number of significant writing assignments. This course is recommended for juniors and seniors. Students may not receive credit for both RBE 3100 and RBE 31 OX.
RBE 4322. Modeling and Analysis of Mechatronic Systems
Cat I (offered at least 1x per Year).
This course introduces students to the modeling and analysis of mechatronic systems. Creation of dynamic models and analysis of model response using the bond graph modeling language are emphasized. Lecture topics include energy storage and dissipation elements, transducers, transformers, formulation of equations for dynamic systems, time response of linear systems, and system control through open and closed feedback loops. Computers are used extensively for system modeling, analysis, and control. Hands-on projects will include the reverse engineering and modeling of various physical systems. Physical models may sometimes also be built and tested.
RBE 4540. Vision-based Robotic Manipulation
Cat I (offered at least 1x per Year).
This course focuses on the role of visual sensing in robotic manipulation. It covers fundamental manipulation concepts such as mathematical grasp formulations, grasp taxonomies, and grasp stability metrics. Various grasp planning strategies in the literature are studied. 2D and 3D vision-based control algorithms are covered. Point cloud processing techniques that allow object detection, segmentation, and feature extraction are studied and implemented. Students will integrate all of these aspects to design the whole vision-based robotic manipulation pipeline.
Students cannot receive credit for both 450X and 4540.
RBE 4601. Human Factors and Human-Robot Interface
Cat I (offered at least 1x per Year).
This is an introductory course on human-robot interaction. It will introduce the behavior and preference of human motor control and motor learning, and how they influence the design of human-robot interface and the dynamics of human-robot interaction. Students will also learn how to conduct human movement studies and social science studies for the design and evaluation of human-robot interfaces. Students in this course will work on interdisciplinary projects, which may involve working with experts in robotics, social science, nursing, and education.
RBE 460X. HUMAN FACTORS AND HUMAN-ROBOT INTERFACE
This is an introductory course on human-robot interaction, offered to first year graduate students and senior undergraduate students. It will introduce (1) the behavior and preference of human motor control and motor learning, and (2) how they influence the design of human-robot interface and the dynamics of human-robot interaction. Students will also learn how to conduct human movement studies and social science studies for the design and evaluation of human-robot interfaces. Students in this course will work on interdisciplinary projects, with the experts in robotics, social science, nursing, and education.
RBE 4701. Artificial Intelligence for Robotics
Cat II (offered at least every other Year).
This is an introductory course covering topics in artificial intelligence that are most relevant to robotics applications. Students will learn techniques for perception, planning, and actuation including: (i) informed, uninformed, and adversarial search; (ii) reasoning with uncertainty; (iii) reinforcement learning; and (iv) deep learning. The course will include a series of laboratories culminating in a final project on perception and navigation in a dynamic environment.
RBE 4815. Industrial Robotics
Cat I (offered at least 1x per Year).
Throughout this course, students will be introduced to industrial robots and their applications. The course covers both industrial serial arm robots, such as those equipped with spherical wrist, and industrial parallel manipulators, such as the Stewart-Gough platform and Delta manipulator. Topics include mechanisms degrees of freedom, inverse and forward kinematics (position and velocity), workspace, singularity, and manipulability analysis of industrial manipulators. Topics may extend to end effectors, motion accuracy, robot control and automation. This course is a combination of lecture, laboratory and project work. Students will engage in practical, hands-on learning experiences through the use of an industrial robot to apply theoretical knowledge to real-world scenarios, fostering comprehensive mastery of industrial robotics principles. Through the laboratory work, students will become familiar with industrial robotic programming while acquiring skills in working with industrial controllers such as Programmable Logic Controllers (PLC).
Graduate Courses
BME 520. Biomechanics and Robotics
This course introduces Biomechanics and Robotics as a unified subject addressing living and man-made organisms. It draws deep connections between the natural and the synthetic, showing how the same principles apply to both, starting from sensing, through control, to actuation. Those principles are illustrated in several domains, including locomotion, prosthetics, and medicine. The following topics are addressed: Biological and Artificial sensors, actuators and control, Orthotics Biomechanics and Robotics, Prosthetic Biomechanics and Robotics: Artificial Organs and Limbs, Rehabilitation Robotics and Biomechanics: Therapy, Assistance and Clinical Evaluation, Human-Robot Interaction and Robot Aided Living for Healthier Tomorrow, Sports, Exercise and Games: Biomechanics and Robotics, Robot-aided Surgery, Biologically Inspired Robotics and Micro- (bio) robotics, New Technologies and Methodologies in Medical Robotics and Biomechanics, Neural Control of Movement and Robotics Applications, Applied Musculoskeletal Models and Human Movement Analysis. This course meshes physics, biology, medicine and engineering and introduce students to subject that holds a promise to be one of the most influential innovative research directions defining the 21st century.
BME 580. Biomedical Robotics
This course will provide an overview of a multitude of biomedical applications of robotics. Applications covered include: image-guided surgery, percutaneous therapy, localization, robot-assisted surgery, simulation and augmented reality, laboratory and operating room automation, robotic rehabilitation, and socially assistive robots. Specific subject matter includes: medical imaging, coordinate systems and representations in 3D space, robot kinematics and control, validation, haptics, teleoperation, registration, calibration, image processing, tracking, and human-robot interaction.Topics will be discussed in lecture format followed by interactive discussion of related literature. The course will culminate in a team project covering one or more of the primary course focus areas. Students cannot receive credit for this course if they have taken the Special Topics (ME 593U) version of the same course.
CS 526. Human-Robot Interaction
This course focuses on human-robot interaction and social robot learning, exploring the leading research, design principles and technical challenges we face in developing robots capable of operating in real-world human environments. The course will cover a range of multidisciplinary topics, including physical embodiment, mixed-initiative interaction, multi-modal interfaces, human-robot teamwork, learning algorithms, aspects of social cognition, and long-term interaction. These topics will be pursued through independent reading, class discussion, and a final project.
CS 549. Computer Vision
This course examines current issues in the computer implementation of visual perception. Topics include image formation, edge detection, segmentation, shape-from-shading, motion, stereo, texture analysis, pattern classification and object recognition. We will discuss various representations for visual information, including sketches and intrinsic images.
ME 527. Foundations of Robotics
Fundamentals of robotics engineering. Topics include forward and inverse kinematics, velocity kinematics, introduction to dynamics and control theory, sensors, actuators, basic probabilistic robotics concepts, fundamentals of computer vision, and robot ethics. In addition, modular robot programming will be covered, and the concepts learned will be applied using realistic simulators.
ME 528. Robot Dynamics
Foundations and principles of robot dynamics. Topics include system modeling including dynamical modeling of serial arm robots using Newton and Lagranges techniques, dynamical modeling of mobile robots, introduction to dynamics-based robot control, as well as advanced techniques for serial arm forward kinematics, trajectory planning, singularity and manipulability, and vision-based control. In addition, dynamic simulation techniques will be covered to apply the concepts learned using realistic simulators. An end of term team project would allow students to apply mastery of the subject to real-world robotic platforms.
RBE 500. Foundations of Robotics
Fundamentals of robotics engineering. Topics include forward and inverse kinematics, velocity kinematics, introduction to dynamics and control theory, sensors, actuators, basic probabilistic robotics concepts, fundamentals of computer vision, and robot ethics. In addition, modular robot programming will be covered, and the concepts learned will be applied using realistic simulators.
RBE 501. Robot Dynamics
Foundations and principles of robot dynamics. Topics include system modeling including dynamical modeling of serial arm robots using Newton and Lagranges techniques, dynamical modeling of mobile robots, introduction to dynamics-based robot control, as well as advanced techniques for serial arm forward kinematics, trajectory planning, singularity and manipulability, and vision-based control. In addition, dynamic simulation techniques will be covered to apply the concepts learned using realistic simulators. An end of term team project would allow students to apply mastery of the subject to real-world robotic platforms.
RBE 502. Robot Control
This course demonstrates the synergy between the control theory and robotics through applications and provides an in-depth coverage of control of manipulators and mobile robots. Topics include linearization, state space modeling and control of linear and nonlinear systems, feedback control, Lyapunov stability analysis of nonlinear control systems, set-point control, trajectory and motion control, compliance and force control, impedance control, adaptive robot control, robust control, and other advanced control topics. Course projects will emphasize simulation and practical implementation of control systems for robotic applications.
RBE 510. Multi-Robot Systems
This course covers the foundation and principles of multi-robot systems. The course will cover the development of the field and provide an overview on different control architectures (deliberative, reactive, behavior-based and hybrid control), control topologies, and system configurations (cellular automata, modular robotic systems, mobile sensor networks, swarms, heterogeneous systems). Topics may include, but are not limited to, multi-robot control and connectivity, path planning and localization, sensor fusion and robot informatics, task-level control, and robot software system design and implementation. These topics will be pursued through independent reading, class discussion, and a course project. The course will culminate in a group project focusing on a collaborative/cooperative multi-robot system. The project may be completed through simulation or hands-on experience with available robotic platforms. Groups will present their work and complete two professional-quality papers in IEEE format. Students cannot receive credit for this course if they have taken the Special Topics (ME 593S) version of the same course.
RBE 511. Swarm Intelligence
This course will cover a wide range of topics in swarm intelligence, including mathematical, computational, and biological aspects. The course is organized in four parts. In the first part, the students will learn about complex systems and the basic concepts of self-organization, such as positive and negative feedback, symmetry breaking, and emergence. The second part concerns several types of network models, such as information cascades, epidemics, and voting. The instructor will illustrate a diverse collection of self-organized systems in nature, finance, and technology that concretize these concepts. The third part is dedicated to swarm robotics, and will cover common swarm algorithms for task allocation, collective motion, and collective decisionmaking. The fourth and final part covers optimization algorithms inspired by swarm intelligence, namely ant colony optimization and particle swarm optimization. The course will blend theory and practice, challenging the students to learn by implementing the algorithms discussed in class through a final project in swarm robotics.
RBE 520. Biomechanics and Robotics
This course introduces Biomechanics and Robotics as a unified subject addressing living and man-made organisms. It draws deep connections between the natural and the synthetic, showing how the same principles apply to both, starting from sensing, through control, to actuation. Those principles are illustrated in several domains, including locomotion, prosthetics, and medicine. The following topics are addressed: Biological and Artificial sensors, actuators and control, Orthotics Biomechanics and Robotics, Prosthetic Biomechanics and Robotics: Artificial Organs and Limbs, Rehabilitation Robotics and Biomechanics: Therapy, Assistance and Clinical Evaluation, Human-Robot Interaction and Robot Aided Living for Healthier Tomorrow, Sports, Exercise and Games: Biomechanics and Robotics, Robot-aided Surgery, Biologically Inspired Robotics and Micro- (bio) robotics, New Technologies and Methodologies in Medical Robotics and Biomechanics, Neural Control of Movement and Robotics Applications, Applied Musculoskeletal Models and Human Movement Analysis. This course meshes physics, biology, medicine and engineering and introduce students to subject that holds a promise to be one of the most influential innovative research directions defining the 21st century.
RBE 521. Legged Robotics
Foundations and principles of parallel manipulators and legged robots. Topics include advanced spatial/3D kinematics and dynamics of parallel manipulators and legged robots including workspace analysis, inverse and forward kinematics and dynamics, motion analysis and control, and gait and stability/balance analysis of legged robots. The course will be useful for solving problems dealing with parallel manipulators as well as multi-legged robots including, but not limited to, quadruped robots, hexapod robots and any other types of multi-legged robots. A final term project allows students to show mastery of the subject by designing, analyzing, and simulating parallel and/or legged robots of their choice.
RBE 522. Continuum Robotics
Continuum robotics focuses on the study of continuously flexible robotic arms. This branch of robotics takes inspiration from flexible animal appendages (e.g., elephant trunks and octopus tentacles) to create manipulato rs capable of complex bending motions. Real-world applications of continuum robots include minimally invasive surgery, industrial inspection, and more generally any scenario that requires manipulation within highly unstructured, confined environments, where traditional rigid-link robotic arms are not suitable for use. This course introduces students to fundamental topics in continuum robot design, modeling, and control. The course culminates in the development of a continuum robot simulator, where students apply the concepts learned in the classroom. Continuum robot platforms will also be available for laboratory/experimental work.
RBE 526. Human-Robot Interaction
This course focuses on human-robot interaction and social robot learning, exploring the leading research, design principles and technical challenges we face in developing robots capable of operating in real-world human environments. The course will cover a range of multidisciplinary topics, including physical embodiment, mixed-initiative interaction, multi-modal interfaces, human-robot teamwork, learning algorithms, aspects of social cognition, and long-term interaction. These topics will be pursued through independent reading, class discussion, and a final project.
RBE 530. Soft Robotics
Soft robotics studies intelligent machines and devices that incorporate some form of compliance in their mechanics. Elasticity is not a byproduct but an integral part of these systems, responsible for inherent safety, adaptation and part of the computation in this class of robots. This course will cover a number of major topics of soft robotics including but not limited to design and fabrication of soft systems, elastic actuation, embedded intelligence, soft robotic modeling and control, and fluidic power. Students will implement new design and fabrication methodologies of soft robots, read recent literature in the field, and complete a project to supplement the course material. Existing soft robotic platforms will be available for experimental work.
RBE 533. Smart Materials & Actuation
This hands on course covers smart materials and actuation, with an emphasis on electroactive polymer (EAP) based materials and actuators, such as contractile EAPs, dielectric elastomers (DEAs), and ion-polymer metal composites (IPMCs). Piezoelectric materials and shape memory alloys (SMAs) are included in the course, as well as pneumatic actuation. Because smart materials and electroactivity are relatively new fields, the course involves literature reviews. Each team project will involve two different types of smart materials, where at least one smart material is electroactive. For the team projects, the class will be organized into groups, ensuring that each group had a mixture of different disciplines to promote lively discussion. Two papers will be required, one as a literature review and one about aspects of the team project. Much of the theory and applied research is yet to be done with smart materials, so this is a very creative course that implements design into the projects, which can include biomimicry.
RBE 535. Printable Robotics
This graduate-level course provides an in-depth examination of 3D printing technologies tailored for the creation of fluidically-driven robotic systems with a focus on design, fabrication, modeling, and control mechanisms. The curriculum encompasses a range of topics, such as fused deposition modeling using thermoplastic polyurethanes, advanced multi-material printing techniques, the engineering of impermeable material systems, and the design of fluidic actuators. The course also covers the fabrication of printable fluidic transistors, the integration of volatile and non-volatile memory elements, and the development of both combinational and sequential fluidic logic circuits, including fluidic state machines. Instruction in COMSOL multi-physics simulation will equip students to correlate empirical observations with numerical data. The course structure includes weekly lectures complemented by hands-on laboratory assignments, where student groups will gain practical experience using cost-effective FDM printers. The course is particularly well-suited for students seeking to deepen their understanding of 3D printing, those interested in constructing their own robotic systems, or individuals aiming to conduct research in the fields of soft robotics, robotic materials, or printable robotics.
RBE 544. Imaging for Medical Robotics
This course aims to introduce the physical principles behind modern medical imaging, including radiography, X-ray computed tomography, nuclear medicine, ultrasound imaging, and magnetic resonance imaging, and their adaptation for image-guided interventions. In robotics, vision and perception play a crucial role, but the optical camera provides only surface information, which limits its usefulness in medical robotics for surgical guidance and diagnosis. To perceive the structural and functional information inside the body, medical imaging is a critical component. Topics include mathematical and physical foundations of each modality, including their interactions with biological tissue. Additionally, the course will present advanced imaging solutions that combine with robotic instrumentation to enable robotic-assisted imaging and image-guided robotic interventions. In the team project, students will tackle real clinical challenges using novel imaging and instrumentation methods.
RBE 549. Computer Vision
This course examines current issues in the computer implementation of visual perception. Topics include image formation, edge detection, segmentation, shape-from-shading, motion, stereo, texture analysis, pattern classification and object recognition. We will discuss various representations for visual information, including sketches and intrinsic images.
RBE 550. Motion Planning
Motion planning is the study of algorithms that reason about the movement of physical or virtual entities. These algorithms can be used to generate sequences of motions for many kinds of robots, robot teams, animated characters, and even molecules. This course will cover the major topics of motion planning including (but not limited to) planning for manipulation with robot arms and hands, mobile robot path planning with non-holonomic constraints, multi-robot path planning, high-dimensional sampling-based planning, and planning on constraint manifolds. Students will implement motion planning algorithms in open-source frameworks, read recent literature in the field, and complete a project that draws on the course material. The PR2 robot will be available as a platform for class projects. Physical robot platforms will be available for class projects.
RBE 575. Safety and Guarantees for Autonomous Robots
Robotic and AI systems have strong potential to directly impact our well-being, from self-driving cars to medical robots. Therefore, it is important to consider strong guarantees on the correctness and safety of their behavior. These guarantees ensure the robot will execute the desired behavior and will not execute undesired behavior. The course will define formal notions of system properties such as safety and liveness, explain how to model and analyze those properties in systems that make decisions and act on them, and understand the specific challenges related to making guarantees on embodied AI systems. This course will cover many topics related to formal guarantees of safety and correctness in robotic and AI systems, including temporal logic-based planning, safe control via invariants and control barrier functions, neural net verification, closed loop control with machine learning components, safe reinforcement learning, and other state-ofthe-art topics at the intersection of safety, guarantees, AI, and robotics.
RBE 577. Machine Learning for Robotics
This graduate-level course delves into the intersection of machine learning and robotics. The curriculum will explore the integration of contemporary learning techniques in robotic areas such as manipulation, navigation, planning, control, decision-making, and other pertinent challenges in robotics. Advanced deep learning techniques and their applications in robotics will be covered, including supervised learning (e.g., behavioral cloning, state prediction), reinforcement learning (e.g., actor-critic, visual foresight), and unsupervised/self-supervised methods (e.g., world model construction, learning forward dynamic models). In addition, the generalizability of these methods will be discussed, recent, and experimental studies will be conducted, examining the challenges of applying these techniques on physical systems.
RBE 580. Biomedical Robotics
This course will provide an overview of a multitude of biomedical applications of robotics. Applications covered include: image-guided surgery, percutaneous therapy, localization, robot-assisted surgery, simulation and augmented reality, laboratory and operating room automation, robotic rehabilitation, and socially assistive robots. Specific subject matter includes: medical imaging, coordinate systems and representations in 3D space, robot kinematics and control, validation, haptics, teleoperation, registration, calibration, image processing, tracking, and human-robot interaction.Topics will be discussed in lecture format followed by interactive discussion of related literature. The course will culminate in a team project covering one or more of the primary course focus areas.
RBE 593. Directed Research for Capstone Experience
Cat I.
This course is for M.S. students who plan to use Directed Research to satisfy their Capstone Experience requirement. To count for the Capstone Experience requirement, the project must be approved by the project advisor at the start of the semester. The project advisor must be affiliated with Robotics Engineering. The project must include substantial analysis and/or design and conclude with a written report and a public presentation.
RBE 594. Capstone Project Experience in Robotics Engineering
This project-based course integrates robotics engineering theory and practice, and provides the opportunity to apply the skills and knowledge acquired in the Robotics Engineering curriculum. The project is normally conducted in teams of two to four students. Students are encouraged to select projects with practical significance to their current and future professional responsibilities. The projects are administered, advised, and evaluated by WPI faculty as part of the learning experience, but students are also encouraged to seek mentorship from experienced colleagues in the Robotics Engineering profession. The project will include substantial analysis and/or design and conclude with a written report and a public presentation.
RBE 595. Special Topics
Arranged by individual faculty with special expertise, these courses survey fundamentals in areas that are not covered by the regular Robotics Engineering course offerings. Exact course descriptions are disseminated by the Robotics Engineering Program well in advance of the offering.
RBE 596. Robotics Engineering Practicum
This practicum provides an opportunity to put into practice the principles studied in previous courses. It will generally be conducted off campus and will involve real-world robotics engineering. Overall conduct of the practicum will be supervised by a WPI RBE faculty member; an on-site liaison will direct day-to-day activity. For a student from industry, a practicum may be sponsored by his or her employer. The project must include substantial analysis and/or design related to Robotics Engineering and will conclude with a substantial written report. There can be no confidential or proprietary company information in the project. A public oral presentation must also be made, to both the host organization and a committee consisting of the supervising faculty member, the on-site liaison and one additional WPI faculty member. This committee will verify successful completion of the practicum.
RBE 598. Directed Research
For M.S. or Ph.D. students wishing to gain research experience peripheral to their thesis topic, M.S. students undertaking a capstone design project*, or doctoral students wishing to obtain research credit prior to admission to candidacy. For Directed Research to count for the Master's capstone experience requirement, the student must enroll in 3 credits for the chosen semester and the project must be approved by the project advisor at the start of the semester. The project advisor must be affiliated with Robotics Engineering. The project must include substantial analysis and/or design and conclude with a written report and a public presentation.*Starting Fall 2024, M.S. students looking to do the capstone experience should register for RBE 593