Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Grannen, Jennifer"'
We introduce Vocal Sandbox, a framework for enabling seamless human-robot collaboration in situated environments. Systems in our framework are characterized by their ability to adapt and continually learn at multiple levels of abstraction from divers
Externí odkaz:
http://arxiv.org/abs/2411.02599
Key to rich, dexterous manipulation in the real world is the ability to coordinate control across two hands. However, while the promise afforded by bimanual robotic systems is immense, constructing control policies for dual arm autonomous systems bri
Externí odkaz:
http://arxiv.org/abs/2309.01087
A robotic feeding system must be able to acquire a variety of foods. Prior bite acquisition works consider single-arm spoon scooping or fork skewering, which do not generalize to foods with complex geometries and deformabilities. For example, when ac
Externí odkaz:
http://arxiv.org/abs/2211.14652
Autor:
Shaikewitz, Lorenzo, Wu, Yilin, Belkhale, Suneel, Grannen, Jennifer, Sundaresan, Priya, Sadigh, Dorsa
Assistance during eating is essential for those with severe mobility issues or eating risks. However, dependence on traditional human caregivers is linked to malnutrition, weight loss, and low self-esteem. For those who require eating assistance, a s
Externí odkaz:
http://arxiv.org/abs/2211.12705
Autor:
Chachra, Gaurav, Kong, Qingkai, Huang, Jim, Korlakunta, Srujay, Grannen, Jennifer, Robson, Alexander, Allen, Richard
Publikováno v:
Sci Rep 12, 8968 (2022)
After significant earthquakes, we can see images posted on social media platforms by individuals and media agencies owing to the mass usage of smartphones these days. These images can be utilized to provide information about the shaking damage in the
Externí odkaz:
http://arxiv.org/abs/2110.05762
Autor:
Sundaresan, Priya, Grannen, Jennifer, Thananjeyan, Brijen, Balakrishna, Ashwin, Ichnowski, Jeffrey, Novoseller, Ellen, Hwang, Minho, Laskey, Michael, Gonzalez, Joseph E., Goldberg, Ken
Robot manipulation for untangling 1D deformable structures such as ropes, cables, and wires is challenging due to their infinite dimensional configuration space, complex dynamics, and tendency to self-occlude. Analytical controllers often fail in the
Externí odkaz:
http://arxiv.org/abs/2107.08942
Autor:
Viswanath, Vainavi, Grannen, Jennifer, Sundaresan, Priya, Thananjeyan, Brijen, Balakrishna, Ashwin, Novoseller, Ellen, Ichnowski, Jeffrey, Laskey, Michael, Gonzalez, Joseph E., Goldberg, Ken
Disentangling two or more cables requires many steps to remove crossings between and within cables. We formalize the problem of disentangling multiple cables and present an algorithm, Iterative Reduction Of Non-planar Multiple cAble kNots (IRON-MAN),
Externí odkaz:
http://arxiv.org/abs/2106.02252
Autor:
Grannen, Jennifer, Sundaresan, Priya, Thananjeyan, Brijen, Ichnowski, Jeffrey, Balakrishna, Ashwin, Hwang, Minho, Viswanath, Vainavi, Laskey, Michael, Gonzalez, Joseph E., Goldberg, Ken
Publikováno v:
4th Conference on Robot Learning (CoRL 2020)
Untangling ropes, wires, and cables is a challenging task for robots due to the high-dimensional configuration space, visual homogeneity, self-occlusions, and complex dynamics. We consider dense (tight) knots that lack space between self-intersection
Externí odkaz:
http://arxiv.org/abs/2011.04999
Autor:
Ganapathi, Aditya, Sundaresan, Priya, Thananjeyan, Brijen, Balakrishna, Ashwin, Seita, Daniel, Grannen, Jennifer, Hwang, Minho, Hoque, Ryan, Gonzalez, Joseph E., Jamali, Nawid, Yamane, Katsu, Iba, Soshi, Goldberg, Ken
Robotic fabric manipulation is challenging due to the infinite dimensional configuration space, self-occlusion, and complex dynamics of fabrics. There has been significant prior work on learning policies for specific deformable manipulation tasks, bu
Externí odkaz:
http://arxiv.org/abs/2003.12698
Autor:
Sundaresan, Priya, Grannen, Jennifer, Thananjeyan, Brijen, Balakrishna, Ashwin, Laskey, Michael, Stone, Kevin, Gonzalez, Joseph E., Goldberg, Ken
Publikováno v:
2020 International Conference on Robotics and Automation
Robotic manipulation of deformable 1D objects such as ropes, cables, and hoses is challenging due to the lack of high-fidelity analytic models and large configuration spaces. Furthermore, learning end-to-end manipulation policies directly from images
Externí odkaz:
http://arxiv.org/abs/2003.01835