On behalf of: Multimedia Archives

2011

Citations in the corpus

• Learning human activities and object affordances from RGB-D videos (2012, neutral): “…more integrated in human environments and are being used in assistive tasks such as automatically interpreting and executing cooking recipes (Bollini et al., 2012), robotic laundry folding (Miller et al., 2011) and arranging a disorganized house (Jiang et al., 2012b; Jiang and Saxena, 2012).”
• SoftGym: Benchmarking Deep Reinforcement Learning for Deformable Object Manipulation (2020, neutral): “We refer to [3] for more details.”
• Sim-to-Real Reinforcement Learning for Deformable Object Manipulation (2018, neutral): “Key domains of interest are home assistance robotics (cloth folding [1], bed making [2], getting dressed [3, 4]); medicine (robot surgery [5], suturing [6]); and industry (cable insertion [7]).”
• kPAM: KeyPoint Affordances for Category-Level Robotic Manipulation (2019, neutral): “In addition, the state-machine [10], [20] and manipulation primitives [24], [13] are specific to the cloth and our manipulation task is out of the scope of these approaches.”
• Modeling, learning, perception, and control methods for deformable object manipulation (2021, unknown): “Accounting for geometry relations of object vertices (40, 55)”
• Learning grounded finite-state representations from unstructured demonstrations (2015, unknown): “Great leaps have been made toward this vision in recent years, to the point that a wide range of robotic behaviors can be programmed, given enough effort; robots now exist that can fold laundry (Miller et al., 2012), play catch (Bauml et al.”
• Visual closed-loop control for pouring liquids (2016, unknown): “The last years have seen dramatic improvements in robotic capabilities relevant to household tasks such as putting items into a dishwasher [1], folding and ironing clothing [2], [3], and cleaning surfaces [4].”
• Robotic manipulation and sensing of deformable objects in domestic and industrial applications: a survey (2018, unknown): “2014) was able to fold clothes much faster, requiring seconds instead of minutes (as in (Miller et al. 2012)).”
• Deep Imitation Learning of Sequential Fabric Smoothing Policies (2019, unknown): “Robot manipulation of fabric has applications in senior care and dressing assistance [11], [12], [13], sewing [41], ironing [21], laundry folding [22], [27], [44], [54], fabric upholstery manufacturing [32], [50], and handling gauze in robotic surgery [48].”