This paper investigates the effectiveness of intent-sharing in enabling maneuver coordination for connected and automated vehicles, demonstrating substantial improvements in two scenarios.

This paper proposes a Fisher information density (FID)-constrained trajectory sharing scheme for robot collision avoidance under GDPR regulations, achieving better privacy-utility tradeoff than fixed-…

The paper introduces CityTrajBench, a unified benchmark framework that standardizes the evaluation of city-scale vehicle trajectory generation, demonstrating that no single generation model dominates…

Proposed an asynchronous block coordinate descent algorithm for distributed trajectory estimation in robotics, reducing communications by up to 96.9% and achieving exponential convergence.

The paper proposes HTP, a novel framework that leverages Large Language Models (LLMs) to first generate abstract travel patterns and then synthesize realistic GPS points, significantly improving traje…

The paper proposes a new paradigm for trajectory forecasting by training models with metric-agnostic probabilistic objectives and optimizing metrics as downstream tasks.

This paper proposes a UAV trajectory optimization framework with continual transfer learning within the O-RAN architecture for 6G cellular systems.

This paper characterizes Pure Nash Equilibria and presents a polynomial-time algorithm for finding them in the Intermittent Strategic Cooperation-Based Two-Agent Path Planning game.

This paper introduces Stigmergic Graph Memory (SGM), a method to improve warehouse throughput in many-to-many Multi-Agent Pickup and Delivery (MAPD) by using a bounded, decaying memory layer to record…

This paper introduces Path Consistency Scoring (PCS), a framework that evaluates router geolocation as a path-level consistency problem and produces a path consistency score based on a Hidden Markov M…

This paper expands the Quality of Control (QoC) framework to address network-induced uncertainties in collaborative robotics, validating the models through experiments on a private 5G testbed.

The paper introduces diffGHOST, a conditional diffusion model that generates synthetic, privacy-preserving mobility trajectories by explicitly mitigating sample memorization in the latent space.

The paper introduces RedundancyBench, a new benchmark for detecting unnecessary steps in LLM agent trajectories, finding that this task is highly complex and difficult to solve.

TraceGraph introduces a graph-based framework to map agent decision-making across pooled trajectories, revealing hidden differences in agent behavior and improving performance by targeting known failu…

The paper proposes BitTP, a lightweight bitlinear architecture that quantizes LLM-based trajectory predictors to 1.58-bit weights while keeping activations full-precision, enabling high-performance de…

The paper proposes a Risk Horizon Profiling (RHP) module that uses a continuous potential field model to profile future risk distributions, significantly improving trajectory prediction accuracy in bo…

The paper proposes a novel four-stage simulation framework that uses GPS-derived seasonal spatial priors and LLMs to generate demographically accurate, synthetic tourist mobility schedules for urban p…