Robotics Domain
Robotics research currently focuses on enhancing robot autonomy, safety, and dexterity, particularly in unstructured environments. Key areas include developing robust control algorithms (like Model Predictive Control and reinforcement learning), improving perception through advanced sensor fusion and generative models, and creating more efficient and adaptable robot designs. These advancements are driving progress in diverse applications such as agriculture, healthcare, and manufacturing, ultimately aiming to create more capable and reliable robots for a wider range of tasks.
Papers
Minimizing Turns in Watchman Robot Navigation: Strategies and Solutions
Hamid Hoorfar, Sara Moshtaghi Largani, Reza Rahimi, Alireza Bagheri
What is the Impact of Releasing Code with Publications? Statistics from the Machine Learning, Robotics, and Control Communities
Siqi Zhou, Lukas Brunke, Allen Tao, Adam W. Hall, Federico Pizarro Bejarano, Jacopo Panerati, Angela P. Schoellig
On Semidefinite Relaxations for Matrix-Weighted State-Estimation Problems in Robotics
Connor Holmes, Frederike Dümbgen, Timothy D Barfoot
Neural radiance fields in the industrial and robotics domain: applications, research opportunities and use cases
Eugen Šlapak, Enric Pardo, Matúš Dopiriak, Taras Maksymyuk, Juraj Gazda
The Michigan Robotics Undergraduate Curriculum: Defining the Discipline of Robotics for Equity and Excellence
Odest Chadwicke Jenkins, Jessy Grizzle, Ella Atkins, Leia Stirling, Elliott Rouse, Mark Guzdial, Damen Provost, Kimberly Mann, Joanna Millunchick