105 citations · 181 across the 16 of their papers we have counts for
16 papers · 1 filter
HALO: High-Altitude Language-Conditioned Monocular Aerial Exploration and Navigation
Yuezhan Tao, Dexter Ong, Fernando Cladera +4
We demonstrate real-time high-altitude aerial metric-semantic mapping and exploration using a monocular camera paired with a global positioning system (GPS) and an inertial measure…
Gaussian Splatting as a Unified Representation for Autonomy in Unstructured Environments
Dexter Ong, Yuezhan Tao, Varun Murali +3
In this work, we argue that Gaussian splatting is a suitable unified representation for autonomous robot navigation in large-scale unstructured outdoor environments. Such environme…
ATLAS Navigator: Active Task-driven LAnguage-embedded Gaussian Splatting
Dexter Ong, Yuezhan Tao, Varun Murali +3
We address the challenge of task-oriented navigation in unstructured and unknown environments, where robots must incrementally build and reason on informative metric-semantic maps…
Monocular Event-Based Vision for Obstacle Avoidance with a Quadrotor
Anish Bhattacharya, Marco Cannici, Nishanth Rao +4
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 env…
RT-GuIDE: Real-Time Gaussian Splatting for Information-Driven Exploration
Yuezhan Tao, Dexter Ong, Varun Murali +3
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 algor…
Hierarchical LLMs In-the-Loop Optimization for Real-Time Multi-Robot Target Tracking under Unknown Hazards
Yuwei Wu, Yuezhan Tao, Peihan Li +4
Real-time multi-robot coordination in hazardous and adversarial environments requires fast, reliable adaptation to dynamic threats. While Large Language Models (LLMs) offer strong…
Safe Interval Motion Planning for Quadrotors in Dynamic Environments
Songhao Huang, Yuwei Wu, Yuezhan Tao +1
Trajectory generation in dynamic environments presents a significant challenge for quadrotors, particularly due to the non-convexity in the spatial-temporal domain. Many existing m…
SlideSLAM: Sparse, Lightweight, Decentralized Metric-Semantic SLAM for Multi-Robot Navigation
Xu Liu, Jiuzhou Lei, Ankit Prabhu +5
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.…
Vision Transformers for End-to-End Vision-Based Quadrotor Obstacle Avoidance
Anish Bhattacharya, Nishanth Rao, Dhruv Parikh +5
We demonstrate the capabilities of an attention-based end-to-end approach for high-speed vision-based quadrotor obstacle avoidance in dense, cluttered environments, with comparison…
An Active Perception Game for Robust Exploration
Siming He, Yuezhan Tao, Igor Spasojevic +2
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., locati…
Trajectory Optimization with Global Yaw Parameterization for Field-of-View Constrained Autonomous Flight
Yuwei Wu, Yuezhan Tao, Igor Spasojevic +1
Trajectory generation for quadrotors with limited field-of-view sensors has numerous applications such as aerial exploration, coverage, inspection, videography, and target tracking…
Learning to Explore Indoor Environments using Autonomous Micro Aerial Vehicles
Yuezhan Tao, Eran Iceland, Beiming Li +7
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 const…
3D Active Metric-Semantic SLAM
Yuezhan Tao, Xu Liu, Igor Spasojevic +2
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 aeria…
SEER: Safe Efficient Exploration for Aerial Robots using Learning to Predict Information Gain
Yuezhan Tao, Yuwei Wu, Beiming Li +4
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…
Experiments in Adaptive Replanning for Fast Autonomous Flight in Forests
Laura Jarin-Lipschitz, Xu Liu, Yuezhan Tao +1
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-c…
Large-scale Autonomous Flight with Real-time Semantic SLAM under Dense Forest Canopy
Xu Liu, Guilherme V. Nardari, Fernando Cladera Ojeda +8
Semantic maps represent the environment using a set of semantically meaningful objects. This representation is storage-efficient, less ambiguous, and more informative, thus facilit…