Probabilistic human intent recognition for shared autonomy in assistive robotics
Effective human-robot collaboration in shared autonomy requires reasoning about the
intentions of the human partner. To provide meaningful assistance, the autonomy has to first …
intentions of the human partner. To provide meaningful assistance, the autonomy has to first …
Reach+ extending the reachability of encountered-type haptics devices through dynamic redirection in vr
Encountered-type haptic devices (EHDs) face a number of challenges when physically
embodying content in a virtual environment, including workspace limits and device latency …
embodying content in a virtual environment, including workspace limits and device latency …
Computer vision in the operating room: Opportunities and caveats
LR Kennedy-Metz, P Mascagni… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
Effectiveness of computer vision techniques has been demonstrated through a number of
applications, both within and outside healthcare. The operating room environment …
applications, both within and outside healthcare. The operating room environment …
Temporal pyramid network for pedestrian trajectory prediction with multi-supervision
Predicting human motion behavior in a crowd is important for many applications, ranging
from the natural navigation of autonomous vehicles to intelligent security systems of video …
from the natural navigation of autonomous vehicles to intelligent security systems of video …
Prediction of sea ice motion with convolutional long short-term memory networks
Prediction of sea ice motion is important for safeguarding human activities in polar regions,
such as ship navigation, fisheries, and oil and gas exploration, as well as for climate and …
such as ship navigation, fisheries, and oil and gas exploration, as well as for climate and …
Robust reinforcement learning: A case study in linear quadratic regulation
This paper studies the robustness of reinforcement learning algorithms to errors in the
learning process. Specifically, we revisit the benchmark problem of discrete-time linear …
learning process. Specifically, we revisit the benchmark problem of discrete-time linear …
Understanding human behaviors in crowds by imitating the decision-making process
Crowd behavior understanding is crucial yet challenging across a wide range of
applications, since crowd behavior is inherently determined by a sequential decision …
applications, since crowd behavior is inherently determined by a sequential decision …
A model predictive control approach for reach redirection in virtual reality
Reach redirection is an illusion-based virtual reality (VR) interaction technique where a
user's virtual hand is shifted during a reach in order to guide their real hand to a physical …
user's virtual hand is shifted during a reach in order to guide their real hand to a physical …
Human intention inference using expectation-maximization algorithm with online model learning
HC Ravichandar, AP Dani - IEEE Transactions on Automation …, 2016 - ieeexplore.ieee.org
An algorithm called adaptive-neural-intention estimator (ANIE) is presented to infer the intent
of a human operator's arm movements based on the observations from a 3-D camera sensor …
of a human operator's arm movements based on the observations from a 3-D camera sensor …
A digital twin-based motion forecasting framework for preemptive risk monitoring
Risk monitoring is a critical task in numerous industrial fields, including construction
engineering. Existing approaches primarily focus on identifying the immediate incidents of …
engineering. Existing approaches primarily focus on identifying the immediate incidents of …