8 accepted papers
Powered wheelchairs provide essential mobility and independence for individuals with motor impairments, yet the skills required for driving and prevalence of safety risks, such as collisions and drop-offs, limit access for users with high levels of disability. Robotic driver assistance systems have …
In robot teleoperation, humans often issue control signals through an interface that requires physical actuation. This interface-level interaction largely goes unmodeled within the field, yet the robot’s interpretation of an interface-level command can differ from what was intended by the user, as a…
A dynamic autonomy allocation framework automatically shifts how much control lies with the human versus the robotics autonomy, for example based on factors such as environmental safety or user preference. To investigate the question of which factors should drive dynamic autonomy allocation, we perf…
We present an assistance system that reasons about a human’s intended actions during robot teleoperation in order to provide appropriate modifications on unintended behavior. Existing methods typically treat the human and control interface as a black box and assume the measured user input is noise-f…
We present a shared control paradigm that improves a user's ability to operate complex, dynamic systems in potentially dangerous environments without a priori knowledge of the user's objective. In this paradigm, the role of the autonomous partner is to improve the general safety of the system withou…
Effective human-robot collaboration in shared control requires reasoning about the intentions of the human user. In this work, we present a mathematical formulation for human intent recognition during assistive teleoperation under shared autonomy. Our recursive Bayesian filtering approach models and…
We present a novel approach to shared control of human-machine systems. Our method assumes no a priori knowledge of the system dynamics. Instead, we learn both the dynamics and information about the user's interaction from observation through the use of the Koopman operator. Using the learned model,…
In this paper, we develop an algorithm for intent inference via goal disambiguation with a shared-control assistive robotic arm. Assistive systems are often required to infer human intent and this often is a bottleneck for providing assistance quickly and accurately. We introduce the notion of inver…