11 accepted papers
Enabling robots to manipulate articulated objects is essential for their successful integration into human-centric environments. Such manipulation is often part of a larger multistep task, where achieving a specific joint configuration is necessary for subsequent actions-for example, in a cluttered …
There are a variety of mechanisms (i.e., input types) for real-time human interaction that can facilitate effective human-robot teaming. For example, previous works have shown how teleoperation, corrective, and discrete (i.e., preference over a small number of choices) input can enable robots to com
Previous methods for Learning from Demonstration leverage several approaches for a human to teach motions to a robot, including teleoperation, kinesthetic teaching, and natural demonstrations. However, little previous work has explored more general interfaces that allow for multiple demonstration ty
Grounding the common-sense reasoning of Large Language Models in physical domains remains a pivotal yet unsolved problem for embodied AI. Whereas prior works have focused on leveraging LLMs directly for planning in symbolic spaces, this work uses LLMs to guide the search of task structures and const…
Shared autonomy methods, where a human operator and a robot arm work together, have enabled robots to complete a range of complex and highly variable tasks. Existing work primarily focuses on one human sharing autonomy with a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http:/
Drones can provide a minimally-constrained adapting camera view to support robot telemanipulation. Furthermore, the drone view can be automated to reduce the burden on the operator during teleoperation. However, existing approaches do not focus on two important aspects of using a drone as an automat…
Remotely programming robots to execute tasks often relies on registering objects of interest in the robot's environment. Frequently, these tasks involve articulating objects such as opening or closing a valve. However, existing human-in-the-loop methods for registering objects do not consider articu…
Many tasks, particularly those involving interaction with the environment, are characterized by high variability, making robotic autonomy difficult. One flexible solution is to introduce the input of a human with superior experience and cognitive abilities as part of a shared autonomy policy. Howeve
Corrective Shared Autonomy is a method where human corrections are layered on top of an otherwise autonomous robot behavior. Specifically, a Corrective Shared Autonomy system leverages an external controller to allow corrections across a range of task variables (e.g., spinning speed of a tool, appli
Manipulations of a constrained object often use a non-rigid grasp that allows the object to rotate relative to the end effector. This orientation slip strategy is often present in natural human demonstrations, yet it is generally overlooked in methods to identify constraints from such demonstrations…