Yuezhan Tao
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View article: Monocular Event-Based Vision for Obstacle Avoidance with a Quadrotor
Monocular Event-Based Vision for Obstacle Avoidance with a Quadrotor Open
We present the first static-obstacle avoidance method for quadrotors using just an onboard, monocular event camera. Quadrotors are capable of fast and agile flight in cluttered environments when piloted manually, but vision-based autonomou…
View article: RT-GuIDE: Real-Time Gaussian Splatting for Information-Driven Exploration
RT-GuIDE: Real-Time Gaussian Splatting for Information-Driven Exploration Open
We propose a framework for active mapping and exploration that leverages Gaussian splatting for constructing dense maps. Further, we develop a GPU-accelerated motion planning algorithm that can exploit the Gaussian map for real-time naviga…
View article: Hierarchical LLMs In-the-Loop Optimization for Real-Time Multi-Robot Target Tracking under Unknown Hazards
Hierarchical LLMs In-the-Loop Optimization for Real-Time Multi-Robot Target Tracking under Unknown Hazards Open
Real-time multi-robot coordination in hazardous and adversarial environments requires fast, reliable adaptation to dynamic threats. While Large Language Models (LLMs) offer strong high-level reasoning capabilities, the lack of safety guara…
View article: Safe Interval Motion Planning for Quadrotors in Dynamic Environments
Safe Interval Motion Planning for Quadrotors in Dynamic Environments Open
Trajectory generation in dynamic environments presents a significant challenge for quadrotors, particularly due to the non-convexity in the spatial-temporal domain. Many existing methods either assume simplified static environments or stru…
View article: SlideSLAM: Sparse, Lightweight, Decentralized Metric-Semantic SLAM for Multi-Robot Navigation
SlideSLAM: Sparse, Lightweight, Decentralized Metric-Semantic SLAM for Multi-Robot Navigation Open
This paper develops a real-time decentralized metric-semantic SLAM algorithm that enables a heterogeneous robot team to collaboratively construct object-based metric-semantic maps. The proposed framework integrates a data-driven front-end …
View article: An Active Perception Game for Robust Information Gathering
An Active Perception Game for Robust Information Gathering Open
Active perception approaches select future viewpoints by using some estimate of the information gain. An inaccurate estimate can be detrimental in critical situations, e.g., locating a person in distress. However the true information gaine…
View article: Trajectory Optimization with Global Yaw Parameterization for Field-of-View Constrained Autonomous Flight
Trajectory Optimization with Global Yaw Parameterization for Field-of-View Constrained Autonomous Flight Open
Trajectory generation for quadrotors with limited field-of-view sensors has numerous applications such as aerial exploration, coverage, inspection, videography, and target tracking. Most previous works simplify the task of optimizing yaw t…
View article: Learning to Explore Indoor Environments using Autonomous Micro Aerial Vehicles
Learning to Explore Indoor Environments using Autonomous Micro Aerial Vehicles Open
In this paper, we address the challenge of exploring unknown indoor aerial environments using autonomous aerial robots with Size Weight and Power (SWaP) constraints. The SWaP constraints induce limits on mission time requiring efficiency i…
View article: 3D Active Metric-Semantic SLAM
3D Active Metric-Semantic SLAM Open
In this letter, we address the problem of exploration and metric-semantic mapping of multi-floor GPS-denied indoor environments using Size Weight and Power (SWaP) constrained aerial robots. Most previous work in exploration assumes that ro…
View article: SEER: Safe Efficient Exploration for Aerial Robots using Learning to Predict Information Gain
SEER: Safe Efficient Exploration for Aerial Robots using Learning to Predict Information Gain Open
We address the problem of efficient 3-D exploration in indoor environments for micro aerial vehicles with limited sensing capabilities and payload/power constraints. We develop an indoor exploration framework that uses learning to predict …
View article: Experiments in Adaptive Replanning for Fast Autonomous Flight in Forests
Experiments in Adaptive Replanning for Fast Autonomous Flight in Forests Open
Fast, autonomous flight in unstructured, cluttered environments such as forests is challenging because it requires the robot to compute new plans in realtime on a computationally-constrained platform. In this paper, we enable this capabili…
View article: Large-Scale Autonomous Flight With Real-Time Semantic SLAM Under Dense Forest Canopy
Large-Scale Autonomous Flight With Real-Time Semantic SLAM Under Dense Forest Canopy Open
Semantic maps represent the environment using a set of semantically\nmeaningful objects. This representation is storage-efficient, less ambiguous,\nand more informative, thus facilitating large-scale autonomy and the\nacquisition of action…