ME:6191 Graduate Seminar

Thursday, January 18 at 3:30 pm to 4:20 pm
Seamans Center, 3505 SC

Enhanced Performance and Autonomy for Field Robots in Unstructured Environments Erkan Kayacan, Ph.D. University of Illinois at Urbana-Champaign, IL, USA Abstract: Nowadays, the complexity in the design of robotic systems increases enormously due to the fact that human beings desire a higher level of intelligence and autonomy. Additionally, it is important that the developed systems must be capable of autonomously adapting to the variations in the operating environment while maintaining the overall objective to accomplish tasks even in highly uncertain and unstructured environments. Such robotic systems must display the ability to learn from experience, adapt themselves to the changing environment and seamlessly integrate information to-and-from humans. Traditional controllers have important limitations: i) inability to tune optimally the coefficients of controllers due to the complex nature and the vaguely known dynamics ii) inability to be able to adapt the control parameters considering changing system parameters and varying environmental conditions iii) inability to deal with constraints on systems iv) not account interactions between subsystems. These drawbacks of traditional control algorithms result in suboptimal control performance of systems. Therefore, advanced techniques are required to deal with naturally constrained, nonlinear, and multi-input-multi-output systems. In this talk, nonlinear model predictive control (NMPC) and nonlinear moving horizon estimation (NMHE), which are computationally very intensive, and require the real-time solution, will be addressed to handle aforementioned problems and their applications in field robots will be shown. Individuals with disabilities are encouraged to attend all University of Iowa sponsored events. If you have a disability that requires an accommodation in order to participate in this program, please call the department in advance, at 335-5668.

Contact Info: MIE Staff,, 335-5939