Zobrazeno 1 - 10
of 7 305
pro vyhledávání: '"A, Mascaro"'
Autor:
Mascaro, Esteve Valls, Lee, Dongheui
As humanoid robots transition from labs to real-world environments, it is essential to democratize robot control for non-expert users. Recent human-robot imitation algorithms focus on following a reference human motion with high precision, but they a
Externí odkaz:
http://arxiv.org/abs/2409.10308
Research continues to accumulate evidence that Goffin's cockatoos (Cacatua goffiniana) can solve wide sets of mechanical problems, such as tool use, tool manufacture, and solving mechanical puzzles. However, the proximate mechanisms underlying this a
Externí odkaz:
http://arxiv.org/abs/2408.05967
This paper addresses the critical need for refining robot motions that, despite achieving a high visual similarity through human-to-humanoid retargeting methods, fall short of practical execution in the physical realm. Existing techniques in the grap
Externí odkaz:
http://arxiv.org/abs/2405.08726
Autor:
Mascaro, Steven, Wu, Yue, Pearson, Ross, Woodberry, Owen, Ramsay, Jessica, Snelling, Tom, Nicholson, Ann E.
COVID-19 appeared abruptly in early 2020, requiring a rapid response amid a context of great uncertainty. Good quality data and knowledge was initially lacking, and many early models had to be developed with causal assumptions and estimations built i
Externí odkaz:
http://arxiv.org/abs/2403.14100
The typical phases of Bayesian network (BN) structured development include specification of purpose and scope, structure development, parameterisation and validation. Structure development is typically focused on qualitative issues and parameterisati
Externí odkaz:
http://arxiv.org/abs/2402.12887
Robot Interaction Behavior Generation based on Social Motion Forecasting for Human-Robot Interaction
Integrating robots into populated environments is a complex challenge that requires an understanding of human social dynamics. In this work, we propose to model social motion forecasting in a shared human-robot representation space, which facilitates
Externí odkaz:
http://arxiv.org/abs/2402.04768
Autor:
Raji, Ayoub, Musiu, Nicola, Toschi, Alessandro, Prignoli, Francesco, Mascaro, Eugenio, Musso, Pietro, Amerotti, Francesco, Liniger, Alexander, Sorrentino, Silvio, Bertogna, Marko
Publikováno v:
2023 IEEE 11th International Conference on Systems and Control (ICSC), Sousse, Tunisia, 2023, pp. 782-789
In this paper, we present a novel formulation to model the effects of a locked differential on the lateral dynamics of an autonomous open-wheel racecar. The model is used in a Model Predictive Controller in which we included a micro-steps discretizat
Externí odkaz:
http://arxiv.org/abs/2312.14808
We consider the problem of learning causal Directed Acyclic Graphs (DAGs) using combinations of observational and interventional experimental data. Current methods tailored to this setting assume that interventions either destroy parent-child relatio
Externí odkaz:
http://arxiv.org/abs/2312.00509
Robots are becoming increasingly integrated into our lives, assisting us in various tasks. To ensure effective collaboration between humans and robots, it is essential that they understand our intentions and anticipate our actions. In this paper, we
Externí odkaz:
http://arxiv.org/abs/2309.16524
This paper introduces a novel deep-learning approach for human-to-robot motion retargeting, enabling robots to mimic human poses accurately. Contrary to prior deep-learning-based works, our method does not require paired human-to-robot data, which fa
Externí odkaz:
http://arxiv.org/abs/2309.05310