Tactile information is essential for contact-rich manipulation tasks in robotics. Vision-based tactile sensors make it particularly easy to design end-to-end manipulation policies with tactile sensing, as they enable the use of existing encoders from computer vision. However, this has led to a huge variety of architect...
Seongjin Bien, Débora Oliveira Makowski, Carlo Kneissl et al.· 0 citations
Memory-dependent manipulation requires robots to make decisions using information that is no longer available to their current sensors, such as recalling an earlier visual cue, tracking task progress, counting repeated events, or estimating elapsed time. We present ReCAT, a language-conditioned policy with structured r...
Pankhuri Vanjani, M. Hatab, Can Mizrakli et al.· 0 citations
HALTER, a Harness for Autonomous Long-horizon Task Evaluation and Reset, which restores the scene by planning over a library of learned atomic reset skills, so demonstration cost scales with the size of that library rather than with the number of terminal states.
Jing Jiang, Yue Yang, Xin-Kai Jiang et al.· 0 citations
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