5 accepted papers
Navigating robots through dynamic multi-robot environments, avoiding collisions with both other robots and obstacles, has emerged as a central challenge in robotics. The existing approaches fall short in allowing the policy network to effectively capture spatial-temporal reciprocal collision avoidan…
Generalizing visual reinforcement learning is fundamental to robot visual navigation, involving the acquisition of a policy from interactions with source environments to facilitate adaptation to analogous, yet unfamiliar target environments. Recent advancements capitalize on data augmentation techni…
Using robots to assist or even replace rescuers for searching and rescuing has always been a research hotspot. Robots that can carry out dexterous operations at the scene are of great significance to reduce the life threat of rescue workers. Aiming at the characteristics of narrow space and frequent
Emotion Recognition in Conversations (ERC) has considerable prospects for developing empathetic machines. For multimodal ERC, it is vital to understand context and fuse modality information in conversations. Recent graph-based fusion methods generally aggregate multimodal information by exploring un…
Pre-trained language models have been widely applied to standard benchmarks. Due to the flexibility of natural language, the available resources in a certain domain can be restricted to support obtaining precise representation. To address this issue, we propose a novel Transformer-based language mod…