Autonomous flight in confined and cluttered environments is fundamentally limited by the restricted field of view (FoV) of onboard sensors. Passive self-rotation expands sensing coverage without additional sensors but introduces a tradeoff between swept-FoV refresh rate and flight performance. This letter presents a configuration-induced passively self-rotating tricopter for perception-enhanced autonomous flight. Firstly, the rear-arm configuration parameter is exploited to regulate the passive self-rotation operating point, providing an airframe-level mechanism for balancing swept-FoV refresh rate and flight performance. Secondly, a hierarchical autonomy framework integrating planning and control is developed to enable agile and robust autonomous flight under continuous passive self-rotation. For waypoint-based inspection, guide-point replanning is further used to improve task-level coverage. Extensive real-world experiments, including high-speed trajectory tracking, disturbance-rejection tests, and autonomous navigation in representative cluttered environments, demonstrate the effectiveness of the proposed approach for perception-enhanced autonomous flight.
Impact hammers, also known as rock-breakers, are essential machines in mining operations, where they perform secondary reduction. In underground mining, these machines are typically teleoperated, limiting operational efficiency. This paper presents a real-time RGB-D perception pi…
This paper presents an innovative design and stability analysis of an underactuated robotic finger with spatial mobility, designed to enhance gripping dexterity in robotic hands. The finger architecture incorporates a revolute joint at its base, enabling passive spatial rotation…
Collaborative-perception enables multi-robot systems to enhance situational awareness by sharing perceptual information. Existing collaborative-perception systems face an inherent trade-off between communication bandwidth requirements and perception accuracy, where methods that e…
DeeperRadar is a radar-centric, sensor-stack-conditioned framework that co-designs radar sensing and multi-modal 3D detection for autonomous mobility by learning a sparse acquisition pattern end-to-end with the fusion model. A learnable MIMO design module is trained end-to-end wi…
In autonomous driving development, a perception dataset is crucial, as it provides fundamental data for training, testing, and validating algorithms for an autonomous vehicle's multimodal perception systems. So far, most research has concentrated on providing datasets for well-st…
Low-cost unmanned ground vehicles are often used in indoor places like warehouses, inspection corridors, and farm rows, where painted floor lines guide the robot. Line following is useful because it only needs one camera and little computing power, but it can fail when the line i…