Zobrazeno 1 - 10
of 7 704
pro vyhledávání: '"Heni, A."'
Autor:
Heni, Rahma
The concept of input-to-state stability (ISS) proposed in the late 1980s is one of the central notions in robust nonlinear control. ISS has become indispensable for various branches of nonlinear systems theory, such as robust stabilization of nonline
Externí odkaz:
http://arxiv.org/abs/2411.08075
This paper introduces a new method for safety-aware robot learning, focusing on repairing policies using predictive models. Our method combines behavioral cloning with neural network repair in a two-step supervised learning framework. It first learns
Externí odkaz:
http://arxiv.org/abs/2411.04408
Effective human-robot collaboration hinges on robust communication channels, with visual signaling playing a pivotal role due to its intuitive appeal. Yet, the creation of visually intuitive cues often demands extensive resources and specialized know
Externí odkaz:
http://arxiv.org/abs/2409.13927
Autor:
Drolet, Michael, Stepputtis, Simon, Kailas, Siva, Jain, Ajinkya, Peters, Jan, Schaal, Stefan, Amor, Heni Ben
Amidst the wide popularity of imitation learning algorithms in robotics, their properties regarding hyperparameter sensitivity, ease of training, data efficiency, and performance have not been well-studied in high-precision industry-inspired environm
Externí odkaz:
http://arxiv.org/abs/2408.06536
Autor:
D'Ambrosio, David B., Abeyruwan, Saminda, Graesser, Laura, Iscen, Atil, Amor, Heni Ben, Bewley, Alex, Reed, Barney J., Reymann, Krista, Takayama, Leila, Tassa, Yuval, Choromanski, Krzysztof, Coumans, Erwin, Jain, Deepali, Jaitly, Navdeep, Jaques, Natasha, Kataoka, Satoshi, Kuang, Yuheng, Lazic, Nevena, Mahjourian, Reza, Moore, Sherry, Oslund, Kenneth, Shankar, Anish, Sindhwani, Vikas, Vanhoucke, Vincent, Vesom, Grace, Xu, Peng, Sanketi, Pannag R.
Achieving human-level speed and performance on real world tasks is a north star for the robotics research community. This work takes a step towards that goal and presents the first learned robot agent that reaches amateur human-level performance in c
Externí odkaz:
http://arxiv.org/abs/2408.03906
We present an open-source library for seamless robot control through motion capture using smartphones and smartwatches. Our library features three modes: Watch Only Mode, enabling control with a single smartwatch; Upper Arm Mode, offering heightened
Externí odkaz:
http://arxiv.org/abs/2406.01117
While imitation learning provides a simple and effective framework for policy learning, acquiring consistent actions during robot execution remains a challenging task. Existing approaches primarily focus on either modifying the action representation
Externí odkaz:
http://arxiv.org/abs/2404.12539
Autor:
Weigend, Fabian C, Liu, Xiao, Sonawani, Shubham, Kumar, Neelesh, Vasudevan, Venugopal, Amor, Heni Ben
This paper introduces iRoCo (intuitive Robot Control) - a framework for ubiquitous human-robot collaboration using a single smartwatch and smartphone. By integrating probabilistic differentiable filters, iRoCo optimizes a combination of precise robot
Externí odkaz:
http://arxiv.org/abs/2403.07199
Large-scale generative models are shown to be useful for sampling meaningful candidate solutions, yet they often overlook task constraints and user preferences. Their full power is better harnessed when the models are coupled with external verifiers
Externí odkaz:
http://arxiv.org/abs/2402.04210
Autor:
Ardianto, Heni, Rosari, Reni
Publikováno v:
International Journal of Workplace Health Management, 2024, Vol. 17, Issue 5/6, pp. 487-502.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IJWHM-02-2024-0027
