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
Computer-Vision Based Real Time Waypoint Generation for Autonomous Vineyard Navigation with Quadruped Robots
Lee Milburn, Juan Gamba, Miguel Fernandes, Claudio Semini
More Than an Arm: Using a Manipulator as a Tail for Enhanced Stability in Legged Locomotion
Huang Huang, Antonio Loquercio, Ashish Kumar, Neerja Thakkar, Ken Goldberg, Jitendra Malik