Zobrazeno 1 - 10
of 251
pro vyhledávání: '"Chernova, Sonia"'
Complex multi-objective missions require the coordination of heterogeneous robots at multiple inter-connected levels, such as coalition formation, scheduling, and motion planning. The associated challenges are exacerbated when solutions to these inte
Externí odkaz:
http://arxiv.org/abs/2404.07902
Object rearrangement is the problem of enabling a robot to identify the correct object placement in a complex environment. Prior work on object rearrangement has explored a diverse set of techniques for following user instructions to achieve some des
Externí odkaz:
http://arxiv.org/abs/2310.00371
As more non-AI experts use complex AI systems for daily tasks, there has been an increasing effort to develop methods that produce explanations of AI decision making that are understandable by non-AI experts. Towards this effort, leveraging higher-le
Externí odkaz:
http://arxiv.org/abs/2309.12482
Proactivity in robot assistance refers to the robot's ability to anticipate user needs and perform assistive actions without explicit requests. This requires understanding user routines, predicting consistent activities, and actively seeking informat
Externí odkaz:
http://arxiv.org/abs/2309.06252
Autor:
Truong, Joanne, Zitkovich, April, Chernova, Sonia, Batra, Dhruv, Zhang, Tingnan, Tan, Jie, Yu, Wenhao
We present IndoorSim-to-OutdoorReal (I2O), an end-to-end learned visual navigation approach, trained solely in simulated short-range indoor environments, and demonstrates zero-shot sim-to-real transfer to the outdoors for long-range navigation on the
Externí odkaz:
http://arxiv.org/abs/2305.01098
Autor:
Patel, Maithili, Chernova, Sonia
Publikováno v:
205:881-891, 2023
Proactive robot assistance enables a robot to anticipate and provide for a user's needs without being explicitly asked. We formulate proactive assistance as the problem of the robot anticipating temporal patterns of object movements associated with e
Externí odkaz:
http://arxiv.org/abs/2211.15501
Robots operating in human environments must be able to rearrange objects into semantically-meaningful configurations, even if these objects are previously unseen. In this work, we focus on the problem of building physically-valid structures without s
Externí odkaz:
http://arxiv.org/abs/2211.04604
Complex, multi-objective missions require the coordination of heterogeneous robots at multiple inter-connected levels, such as coalition formation, scheduling, and motion planning. This challenge is exacerbated by dynamic changes, such as sensor and
Externí odkaz:
http://arxiv.org/abs/2209.13092
If we want to train robots in simulation before deploying them in reality, it seems natural and almost self-evident to presume that reducing the sim2real gap involves creating simulators of increasing fidelity (since reality is what it is). We challe
Externí odkaz:
http://arxiv.org/abs/2207.10821