5 accepted papers
Robot grasping applications are faced with challenges and limitations leading to errors that affect their performance and accuracy. Although these errors are reduced in expensive industrial systems, low-cost robots are still prone to inaccurate perception and execution due to their limited hardware…
Controlling and manning robots from a remote location is difficult because of the limitations one faces in perception and available degrees of actuation. Although humans can become skilled teleoperators, the amount of training time required to acquire such skills is typically very high. In this pape…
In this work, we are proposing an intuitive Augmented SLAM method (A-SLAM) that allows the user to interact, in real-time, with a robot running SLAM to correct for pose and map errors. We built an AR application that works on HoloLens and allows the operator to view the robot's map superposed on the…
In this paper, we are proposing a collaborative SLAM system between a team of three heterogeneous agents: a robot, a human operator, and an augmented reality head mounted display (ARHMD). The system allows for online editing of a map produced by a robot running SLAM. Through hand gestures, the user…
In this paper we develop a real-time human augmented mapping system. This approach replaces the traditional offline post processing of maps by a user-friendly system allowing for online editing capabilities. A wide number of applications that acquire accurate mapping of the environment could benefit…