6 accepted papers
Continuous-time reinforcement learning (CTRL) provides a natural framework for sequential decision-making in dynamic environments where interactions evolve continuously over time. While CTRL has shown growing empirical success, its ability to adapt to varying levels of problem difficulty remains poo…
Continuous-time reinforcement learning (CTRL) provides a principled framework for sequential decision-making in environments where interactions evolve continuously over time. Despite its empirical success, the theoretical understanding of CTRL remains limited, especially in settings with general fun
To foster an immersive and natural human-robot interaction (HRI), the implementation of tactile perception and feedback becomes imperative, effectively bridging the conventional sensory gap. In this paper, we propose a dual-modal electronic skin (e-skin) that integrates magnetic tactile sensing and…
Surface vibration tactile feedback is capable of conveying various semantic information to humans via handheld electronic devices, such as smartphones, touch panels, and game controllers. However, covering the entire contacting surface of the device with a dense arrangement of actuators can affect i…
Cutaneous haptics is helpful to tame the human-machine mismatch by interactive tactile feedback and perform precise manipulations for virtual immersive interactions. However, wearable tactile gloves cover the palm and fingers greatly, thus reducing the tactile information from interactive objects an
Spectral clustering has gained popularity for clustering non-convex data due to its simplicity and effectiveness. It is essential to construct a similarity graph using a high-quality affinity measure that models the local neighborhood relations among the data samples. However, incomplete data can le…