arXiv subjects

Yijie Liao

Publications and source records attributed to Yijie Liao.

5 recordsLinked to original sources

arXiv2026

Deep Reinforcement-Learning-Guided Model Predictive Control for Preventing Overtakes in Autonomous Racing

This paper addresses defensive blocking in autonomous racing, where a vehicle must prevent a faster opponent from overtaking while operating near its dynamic limits. Different from lap-time minimization, we formulate defense as a spatial occupancy regulation problem via a hierarchical reinforcement-learning guided model predictive control framework. A Soft Actor-Critic strategic layer operates in the Frenet domain to generate geometry-aware defensive references, which are embedded into the nonlinear model predictive control formulation as spatial regularization under friction constraints. Evaluated on the Thunderhill West circuit in simulation, the framework increases average overtake time from 8.8 s to 14.6 s while significantly reducing opponent progress. Meanwhile, it allows the vehicle to utilize 83.4% of available tire force. The framework achieves a 33.3 ms mean solve time (13.9 ms std), supporting real-time high-speed adversarial interaction.

cs.RO↗

arXiv2025

Mollow-like triplets in ultra-fast resonant absorption

We show that resonant absorption of smooth laser fields can yield Mollow-like triplet patterns. General conditions for such triplets are derived and illustrated with a super-Gaussian pulse sequence. Gaussian pulses can not exhibit triplets, super-Gaussian pulses can form triplets depending on the pulse area and flat-top pulses can produce absorption triplets after one Rabi cycle. Our results are compared side-by-side with resonance fluorescence to emphasize similarities and differences between these unlike observables. In the high-intensity limit, we show that the central absorption peak is asymmetric, which we attribute to non-linear photoionization, beyond two-level atomic physics.

quant-ph↗

arXiv2025

Search-Based Path Planning in Interactive Environments among Movable Obstacles

This paper investigates Path planning Among Movable Obstacles (PAMO), which seeks a minimum cost collision-free path among static obstacles from start to goal while allowing the robot to push away movable obstacles (i.e., objects) along its path when needed. To develop planners that are complete and optimal for PAMO, the planner has to search a giant state space involving both the location of the robot as well as the locations of the objects, which grows exponentially with respect to the number of objects. This paper leverages a simple yet under-explored idea that, only a small fraction of this giant state space needs to be searched during planning as guided by a heuristic, and most of the objects far away from the robot are intact, which thus leads to runtime efficient algorithms. Based on this idea, this paper introduces two PAMO formulations, i.e., bi-objective and resource constrained problems in an occupancy grid, and develops PAMO*, a planning method with completeness and solution optimality guarantees, to solve the two problems. We then further extend PAMO* to hybrid-state PAMO* to plan in continuous spaces with high-fidelity interaction between the robot and the objects. Our results show that, PAMO* can often find optimal solutions within a second in cluttered maps with up to 400 objects.

cs.RO↗

arXiv2024

IntellectSeeker: A Personalized Literature Management System with the Probabilistic Model and Large Language Model

Faced with the burgeoning volume of academic literature, researchers often need help with uncertain article quality and mismatches in term searches using traditional academic engines. We introduce IntellectSeeker, an innovative and personalized intelligent academic literature management platform to address these challenges. This platform integrates a Large Language Model (LLM)--based semantic enhancement bot with a sophisticated probability model to personalize and streamline literature searches. We adopted the GPT-3.5-turbo model to transform everyday language into professional academic terms across various scenarios using multiple rounds of few-shot learning. This adaptation mainly benefits academic newcomers, effectively bridging the gap between general inquiries and academic terminology. The probabilistic model intelligently filters academic articles to align closely with the specific interests of users, which are derived from explicit needs and behavioral patterns. Moreover, IntellectSeeker incorporates an advanced recommendation system and text compression tools. These features enable intelligent article recommendations based on user interactions and present search results through concise one-line summaries and innovative word cloud visualizations, significantly enhancing research efficiency and user experience. IntellectSeeker offers academic researchers a highly customizable literature management solution with exceptional search precision and matching capabilities. The code can be found here: https://github.com/LuckyBian/ISY5001

cs.IR↗

arXiv2024

Circularly polarized RABBIT applied to a Rabi-cycling atom

We utilize the reconstruction of attosecond beating by interference of two-photon transitions (RABBIT) technique to study the phase of a Rabi-cycling atom using circularly polarized extreme ultraviolet and infrared (IR) fields, where the IR field induces Rabi oscillations between the 2s and 2p states of lithium. Autler-Townes splittings are observed in sidebands of the photoelectron spectra and the relative phases of outgoing electron wave packets are retrieved from the azimuthal angle. In this RABBIT scheme, more ionization pathways beyond the usual two-photon pathways are required. Our results show that the polar-angle-integrated and polar-angle-resolved RABBIT phases have different behaviors when the XUV and IR fields have co- and counter-rotating circular polarizations, which are traced back to the different ionization channels according to the selection rules in these two cases and their competition relying on the propensity rule in laser-assisted photoionization.

physics.atom-ph↗