16 accepted papers
This paper presents the design, modeling, and motion control of BiSTAC, a novel hybrid terrestrial–aerial vehicle. BiSTAC features an innovative configuration that integrates a bicopter propeller system with a flexible bipedal locomotion mechanism, thereby enabling both bicopter flight and bipedal w
Accurate Subseasonal-to-Seasonal (S2S) forecasting is vital for decision-making in agriculture, energy production, and emergency management. However, it remains a challenging and underexplored problem due to the chaotic nature of the weather system. Recent data-driven studies have shown promising re…
Despite recent remarkable achievements in quadruped control, it remains challenging to ensure robust and compliant locomotion in the presence of unforeseen external disturbances. Existing methods prioritize locomotion robustness over compliance, often leading to stiff, high-frequency motions, and en
Reference-based super-resolution (RefSR) has the potential to build bridges across spatial and temporal resolutions of remote sensing images. However existing RefSR methods are limited by the faithfulness of content reconstruction and the effectiveness of texture transfer in large scaling factors. C…
This letter concentrates on the development of Chat-PM, a class of composite hybrid aerial/terrestrial manipulator, in concern with composite configuration design, dynamics modeling, motion control and force estimation. Compared with existing aerial or terrestrial mobile manipulators, Chat-PM demons
Nighttime light (NTL) remote sensing observation serves as a unique proxy for quantitatively assessing progress toward meeting a series of Sustainable Development Goals (SDGs), such as poverty estimation, urban sustainable development, and carbon emission. However, existing NTL observations often su…
Fine urban change segmentation using multi-temporal remote sensing images is essential for understanding human-environment interactions in urban areas. Although there have been advances in high-quality land cover datasets that reveal the physical features of urban landscapes, the lack of fine-graine…
Model-free reinforcement learning (RL) is inherently a reactive method, operating under the assumption that it starts with no prior knowledge of the system and entirely depends on trial-and-error for learning. This approach faces several challenges, such as poor sample efficiency, generalization, an…
Grasping lightweight objects with aerial manipulators remains challenging due to the rotorwash interference caused by spinning rotor blades. This letter details a rotorwash-aware motion planning method for Chat-PM, a hybrid aerial-terrestrial vehicle equipped with a robotic arm. With proposed method
Semi-supervised learning has attracted increasing attention in the large-scale land cover mapping task. However, existing methods overlook the potential to alleviate the class imbalance problem by selecting a suitable set of unlabeled data. Besides, in class-imbalanced scenarios, existing pseudo-lab…
In this study, an NMPC-based planning approach is proposed for Hybrid Terrestrial and Aerial Quadrotors (HyTAQs) to achieve safe and efficient hybrid locomotion in unknown environments. The approach ensures bimodal dynamic feasibility and fully exploits the high efficiency and accessibility of HyTAQ
Terrestrial-aerial bimodal vehicles bloom in both academia and industry because they incorporate both the high mobility of aerial vehicles and the long endurance of ground vehicles. In this work, we present an autonomous and adaptive navigation framework to bring complete autonomy to this class of v
In this study, a topology-guided unified nonlinear model predictive control (NMPC) approach is proposed for autonomous navigation of a class of Hybrid Terrestrial and Aerial Quadrotors (HyTAQs) in unknown environments. The approach can fully exploit the hybrid terrestrial-aerial locomotion of the ve…
This work details the design, modeling and control of SytaB, a vehicle capable of hybrid terrestrial/aerial mobility with smooth transition, where the structure embedding a bicopter is adopted for the first time. In contrast to previous hybrid terrestrial/aerial vehicles with a quadrotor embedded, S
Reinforcement Learning (RL) and its integration with deep learning have achieved impressive performance in various robotic control tasks, ranging from motion planning and navigation to end-to-end visual manipulation. However, stability is not guaranteed in model-free RL by solely using data. From a
The Spring-Loaded Inverted Pendulum (SLIP) has been widely exploited in both biomechanical and robotics research due to its simple form in mathematics and high accuracy in fitting experimental biology data. However the intrinsic nonlinearity of the SLIP dynamics makes accurate analytical representat…