11 accepted papers
Zero-shot object navigation in unknown environments presents significant challenges, mainly due to two key limitations: insufficient semantic guidance leads to inefficient exploration, while limited spatial memory resulting from environmental structure causes entrapment in local regions. To address …
Current wheeled bipedal robots face significant mobility challenges when traversing discontinuous terrain such as gaps and step-like obstacles, and suffer from substantial dynamic inefficiencies. This paper presents a hybrid self-reconfigurable wheel-legged dual-arm robot equipped with an active doc
Reliable semantic segmentation of open environments is essential for intelligent systems, yet significant problems remain: 1) Existing RGB-T semantic segmentation models mainly rely on low-level visual features and lack high-level textual information, which struggle with accurate segmentation when c
The diversity of urban traffic scenarios poses challenges in stability and generalization for autonomous driving. To tackle this issue, this paper proposes a hierarchical decision-making and planning framework based on reinforcement learning, which employs a unified drivable area cross-attention ext
Overlapping sound events are ubiquitous in real-world environments, but existing end-to-end sound event detection (SED) methods still struggle to detect them effectively. A critical reason is that these methods represent overlapping events using shared and entangled frame-wise features, which degrad…
Despite the success of self-supervised respiratory sound classification methods, they do not consider that respiratory sounds are quasi-periodic signals with repetitive patterns in successive breaths, which is vital for distinguishing respiratory sounds from non-quasi-periodic sounds like noises. Th…
Autonomous driving in urban scenarios faces uncertain dynamic changes, especially in China, where a dense mixture of cars, cyclists and pedestrians travel together on roads with random uncertain behaviors and high-risk road crossing. This letter proposes a Multi-step Continuous Decision Making and S
Unknown area exploration is a crucial but challenging task for autonomous driving of unmanned ground vehicles (UGV) in unknown off-road environments. However, the exploration efficiency of a single UGV is low due to its limited sensing range. To solve this problem, this paper proposes a risk-inspire…
Self-supervised depth estimation has attracted much attention due to its ability to improve the 3D perception capabilities of unmanned systems. However, existing unsupervised frameworks rely on the assumption of photometric consistency, which may not hold in challenging environments such as night-ti…
Automated Valet Parking (AVP) has been exten-sively researched as an important application of autonomous driving. Considering the high dynamics and density of real parking lots, a system that considers multiple vehicles simultaneously is more robust and efficient than a single vehicle setting as in…
Respiratory sound classification refers to identifying adventitious sounds from given recordings automatically. Due to the difficulty of collection and the expensive manual annotation, there are only limited samples available, which impacts on learning better models. Meanwhile, a majority of these m…