Robotics and control are two closely related fields, both of which have a rich heritage of intellectual depth and practical achievements. The Robotics and Control area group offers an array of undergraduate and graduate courses in control, robotics, and automation, and conducts vibrant research at the frontier of these fields. For example, in robotics research, faculty research interests span underwater robotics, aerial robotics, autonomous vehicles, and soft robotics; and in controls, faculty research interests include distributed and networked control, learning-based control, game theory, and cyber-physical-human systems. These research activities are often motivated by and evaluated in real-world applications, such as tracking invasive species, autonomous driving, resilience in cyber-physical systems, and underwater search and rescue. Some highlights of faculty research are provided below.
Bio-inspired Robotics (Tan): Taking inspiration from nature, we develop novel robots and explore their applications in environmental monitoring, healthcare, and search and rescue. Our work emphasizes fundamental research while keeping in sight their practical relevance, with an end-to-end cycle of robot design, dynamic modeling, control, and experimentation (often involving field experiments). Examples of our robots include gliding robotic fish for underwater sensing, snake robots for pipeline inspection, and soft robotic gloves for studying motor learning. We are also interested in new smart materials and their application to sensing and actuation.
3D Vision (Morris): We explore the world of 3D sensing using machine learning and artificial intelligence. For example, automated vehicles generate gigabits of data per second. Making sense of this and turning it into useful knowledge can be hard. Our work creates new algorithms for sensor processing (especially Lidar and video) to enable scene modeling and understanding. We are also interested in the application of 3D vision to smart agriculture (e.g., animal detection and tracking, plant photosynthesis distribution assessment) and tremor tracking for Parkinson’s disease patients.
Distributed Cyber Physical Human Systems (Srivastava): Our work focuses on Cyber-Physical-Human Systems (CPHS), which involve several agents, such as humans and robots, interacting over a network to achieve a desired outcome. The goal of our research is the realization of synergistic collaboration of autonomous systems with human partners towards desired goals. To this end, we use control-theoretic techniques towards agent modeling, including cognitive modeling of human agents, as well as analysis and design of shared human-robot multi-agent systems. These efforts often build upon techniques from stochastic optimal control, nonlinear control, and network systems. Our experimental facilities include ground and aerial robotics arena, an open-source swarm testbed, EEG and eye-tracking facilitated human-robot teaming, and haptic tele-operation.
Safe and Resilient Learning-enabled Control (Kiumarsi): The goal is to combine learning, optimization, and safe control, to enable next-generation autonomous systems. In safe learning-enabled control, we aim to integrate performance-oriented control objectives with safety specifications and monitor the system’s learning process to proactively trade-off between safety and performance. In resilient learning-enabled control, we aim to bridge the gap between reinforcement learning-based control design and resilient control design for cyber-physical systems under uncertainty and possible malicious activities.
Secure and Efficient Autonomous Systems (Bopardikar): Our group performs fundamental research in efficient and effective motion planning of autonomous vehicles to achieve complex objectives while guaranteeing security against adversarial attacks. The research topics span multiple disciplines ranging from control theory, game theory, estimation and randomized algorithms. Applications include integrity of current and future autonomous systems (e.g., self-driving cars), environmental monitoring and estimation with limited resources.
Physical Ultrasonics, Microscopy and Acoustics (Chakrapani). Our research focuses on 2D, 3D and 4D imaging of structures for flaws/defects using acoustics/ultrasonics, acoustic microscopy and studying the interaction of ultrasonics waves with discontinuities. 2D imaging allows us to determine the location of the discontinuity, 3D imaging allows us to determine the depth, and 4D imaging allows us to determine the evolution with time. Unlike optical imaging which only provides location, elastic imaging allows us to image the stiffness of the structure as well. We use non-contact, non-invasive methods to develop complete 3D models, and digital twins of the structure. Applications include structural elements such as bridges, pavements; aerospace components such as jet engine, rotor blades etc.; biomedical applications such as tissue; and material characterization.
Courses & Labs:
- ECE 313: Control Systems (3 credits, Lecture)
- ECE 415: Computer Aided Manufacturing (3 credits, Lecture & Lab)
- ECE 416: Digital Control (3 credits, Lecture & Lab)
- ECE 417: Robotics (4 credits, Lecture & Lab)
- ECE 818: Robotics (3 credits, Lecture)
- ECE 819: Smart Material Sensors and Actuators (3 credits, Lecture)
- ECE 851: Linear Systems and Control (3 credits, Lecture)
- ECE 853: Optimal Control (3 credits, Lecture)
- ECE 854: Robust Control (3 credits, Lecture)
- ECE 856: Adaptive Control (3 credits, Lecture)
- ECE 859: Nonlinear Systems and Control (3 credits, Lecture)
- ECE 960C: Networked and Embedded Control Systems (3 credits, Lecture)
Shaunak Bopardikar, Sunil Chakrapani, Bahare Kiumarsi, Daniel Morris, Vaibhav Srivastava, Xiaobo Tan
Secure and Efficient Autonomous Systems Lab (Bopardikar): https://sites.google.com/site/bshaunak/
Physical Ultrasonics, Microscopy and Acoustics (PUMA) Lab (Chakrapani): http://www.egr.msu.edu/~csk/
Learning-enabled Control (Kiumarsi): https://sites.google.com/site/baharekiumarsi
3D Vision Lab (Morris): https://www.egr.msu.edu/3dvision/
Distributed CYber Physical Human systEms Research (D-CYPHER) Lab (Srivastava): https://www.egr.msu.edu/d-cypher/
Open Swarm: https://github.com/MSU-dcypherlab/OpenSwarm
Smart Microsystems Lab (Tan): https://www.egr.msu.edu/~xbtan/sml_index.html