1 code implementation • 24 Apr 2023 • Mingjie Li, Tharindu Rathnayake, Ben Beck, Lingheng Meng, Zijue Chen, Akansel Cosgun, Xiaojun Chang, Dana Kulić
Instance-level detection aims to detect which vehicle in the scene gives rise to a close pass near miss.
1 code implementation • 12 Sep 2022 • Lingheng Meng, Rob Gorbet, Dana Kulić
Deep Reinforcement Learning (DRL) has made tremendous advances in both simulated and real-world robot control tasks in recent years.
no code implementations • 17 Mar 2022 • Rachel Love, Edith Law, Philip R. Cohen, Dana Kulić
The results indicate that teaching via paraphrasing and text input has a positive effect on learning outcomes for the material covered, and also on aspects of affective engagement.
1 code implementation • 24 Feb 2021 • Lingheng Meng, Rob Gorbet, Dana Kulić
A promising characteristic of Deep Reinforcement Learning (DRL) is its capability to learn optimal policy in an end-to-end manner without relying on feature engineering.
1 code implementation • 22 Aug 2020 • Vladimir Joukov, Dana Kulić
Training with the proposed approach requires computing only a $N \times n$ eigenfunction matrix and a $n \times n$ inverse where $n$ is a selected number of eigenvalues.
2 code implementations • 5 Aug 2020 • Wanxin Jin, Todd D. Murphey, Dana Kulić, Neta Ezer, Shaoshuai Mou
The time stamps of the keyframes can be different from the time of the robot's actual execution.
no code implementations • 23 Jun 2020 • Lingheng Meng, Rob Gorbet, Dana Kulić
Recently, research in Deep Reinforcement Learning (DRL) also shows that multi-step methods improve learning speed and final performance in applications where the value-function and policy are represented with deep neural networks.
no code implementations • 2 May 2020 • Shray Bansal, Rhys Newbury, Wesley Chan, Akansel Cosgun, Aimee Allen, Dana Kulić, Tom Drummond, Charles Isbell
We compare two robot modes in a shared table pick-and-place task: (1) Task-oriented: the robot only takes actions to further its own task objective and (2) Supportive: the robot sometimes prefers supportive actions to task-oriented ones when they reduce future goal-conflicts.
no code implementations • 31 Aug 2018 • Muriel Lang, Franz M. J. Pfister, Jakob Fröhner, Kian Abedinpour, Daniel Pichler, Urban Fietzek, Terry T. Um, Dana Kulić, Satoshi Endo, Sandra Hirche
The assessment of Parkinson's disease (PD) poses a significant challenge as it is influenced by various factors which lead to a complex and fluctuating symptom manifestation.
1 code implementation • 8 Aug 2018 • Terry Taewoong Um, Franz Michael Josef Pfister, Daniel Christian Pichler, Satoshi Endo, Muriel Lang, Sandra Hirche, Urban Fietzek, Dana Kulić
Parkinson's Disease (PD) is characterized by disorders in motor function such as freezing of gait, rest tremor, rigidity, and slowed and hyposcaled movements.
1 code implementation • 19 Jun 2018 • Thomas Beckers, Dana Kulić, Sandra Hirche
The model fidelity is used to adapt the feedback gains allowing low feedback gains in state space regions of high model confidence.
2 code implementations • 21 Mar 2018 • Wanxin Jin, Dana Kulić, Shaoshuai Mou, Sandra Hirche
We handle the problem by proposing the recovery matrix, which establishes a relationship between available observations of the trajectory and weights of given candidate features.
Robotics Systems and Control
2 code implementations • 2 Jun 2017 • Terry Taewoong Um, Franz Michael Josef Pfister, Daniel Pichler, Satoshi Endo, Muriel Lang, Sandra Hirche, Urban Fietzek, Dana Kulić
While convolutional neural networks (CNNs) have been successfully applied to many challenging classification applications, they typically require large datasets for training.
no code implementations • 22 Oct 2016 • Terry Taewoong Um, Vahid Babakeshizadeh, Dana Kulić
The ability to accurately identify human activities is essential for developing automatic rehabilitation and sports training systems.