Robot Person
Robot person research focuses on creating robots capable of interacting naturally and effectively with humans, encompassing tasks from simple navigation to complex manipulation and social interaction. Current research emphasizes developing robust control algorithms (like Kalman filters and Model Predictive Control), integrating advanced perception models (including Vision-Language Models and sensor fusion), and improving human-robot interaction through multimodal communication and shared autonomy. This field is significant for advancing robotics capabilities in various sectors, including healthcare, manufacturing, and service industries, by enabling robots to perform tasks more safely, efficiently, and intuitively alongside humans.
Papers
Gaze-Based Intention Recognition for Human-Robot Collaboration
Valerio Belcamino, Miwa Takase, Mariya Kilina, Alessandro Carfì, Akira Shimada, Sota Shimizu, Fulvio Mastrogiovanni
RoboCAP: Robotic Classification and Precision Pouring of Diverse Liquids and Granular Media with Capacitive Sensing
Yexin Hu, Alexandra Gillespie, Akhil Padmanabha, Kavya Puthuveetil, Wesley Lewis, Karan Khokar, Zackory Erickson