209+ open-access research outputs.
Reliable odometry is essential for mobile robots as they increasingly enter more challenging environments, which often contain little information to constrain point cloud registration, resulting in de…
Human-in-the-loop (HITL) UAV operation is essential in complex and safety-critical aerial surveying environments, where human operators provide navigation intent while onboard autonomy must maintain a…
We propose a multimodal deep learning model for VR auralization that generates spatial room impulse responses (SRIRs) in real time to reconstruct scene-specific auditory perception. Employing SRIRs as…
Odometry estimation using light detection and ranging (LiDAR) and an inertial measurement unit (IMU), known as LiDAR-inertial odometry (LIO), often suffers from performance degradation in degenerate e…
We study the problem of controlling how a limited communication bandwidth budget is allocated across heterogeneously quantized sensor measurements. The performance criterion is the trace of the error …
Light detection and ranging (LiDAR)-inertial odometry (LIO) enables accurate localization and mapping for autonomous navigation in various scenes. However, its performance remains sensitive to variati…
In estimating odometry accurately, an inertial measurement unit (IMU) is widely used owing to its high-rate measurements, which can be utilized to obtain motion information through IMU propagation. In…
Robust and accurate navigation is critical for Unmanned Aerial Vehicles (UAVs) especially for those with stringent Size, Weight, and Power (SWaP) constraints. However, most state-of-the-art (SOTA) LiD…
Recently, affine frequency division multiplexing (AFDM) has gained traction as a robust solution for doubly selective channels. In this paper, we present a novel low-complexity one-tap equalizer for z…
Task planning for mobile robots often assumes full environment knowledge and so popular approaches, like planning via the PDDL, cannot plan when the locations of task-critical objects are unknown. Rec…
In this study, we address vision-language-guided multi-robot cooperative transport, where each robot grounds natural-language instructions from onboard camera observations. A key challenge in this dec…
Cell-free networks leverage distributed access points (APs) to achieve macro-diversity, yet their performance is often constrained by large disparities in channel quality arising from user geometry an…
Accurate calibration and robust localization are fundamental for downstream tasks in spinning actuated LiDAR applications. Existing methods, however, require parameterizing extrinsic parameters based …
This paper introduces an adaptive preprocessing technique to enhance the accuracy of channel state information-based physical layer authentication (CSI-PLA) alleviating CSI variations and inconsistenc…
The development and evaluation of Lidar-Inertial Odometry (LIO) and Simultaneous Localization and Mapping (SLAM) systems requires a precise ground truth. The Global Navigation Satellite System (GNSS) …
Monitoring contact pressure in hospital beds is essential for preventing pressure ulcers and enabling real-time patient assessment. Current methods can predict pressure maps but often lack physical pl…
Autonomous navigation in unstructured environments requires robots to assess terrain difficulty in real-time and plan paths that balance efficiency with safety. This thesis presents a traversability-a…
Critical maritime infrastructure increasingly demands situational awareness both above and below the surface, yet existing ''seabed-to-sky'' mapping pipelines either rely on GNSS (vulnerable to shadow…
LiDAR-inertial odometry (LIO) is an active research area, as it enables accurate real-time state estimation in GPS-denied environments. Recent advances in map data structures and spatial indexing have…
This work addresses electric vehicle (EV) charging station placement through a bi-level optimization model, where the upper-level planner maximizes net revenue by selecting station locations under bud…
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