activity
20242026
collaborators

6 papers

cs.LG2026

Lagrangian Perturbation Diffusion Steering: Latent Reinforcement Learning for Generative Policies

Hikmet Simsir, Ozgur S. Oguz

Behavior cloning with high-capacity generative policies achieves strong imitation performance, but is often limited by demonstration coverage and distribution shift. Direct reinfor…

cs.RO2026

Interpretable Responsibility Sharing as a Heuristic for Task and Motion Planning

Arda Sarp Yenicesu, Sepehr Nourmohammadi, Berk Cicek +1

This article introduces a novel heuristic for Task and Motion Planning (TAMP) named Interpretable Responsibility Sharing (IRS), which enhances planning efficiency in domestic robot…

cs.RO2025

SeGMan: Sequential and Guided Manipulation Planner for Robust Planning in 2D Constrained Environments

Cankut Bora Tuncer, Dilruba Sultan Haliloglu, Ozgur S. Oguz

In this paper, we present SeGMan, a hybrid motion planning framework that integrates sampling-based and optimization-based techniques with a guided forward search to address comple…

cs.LG2024

Locally Adaptive One-Class Classifier Fusion with Dynamic p-Norm Constraints for Robust Anomaly Detection

Sepehr Nourmohammadi, Arda Sarp Yenicesu, Shervin Rahimzadeh Arashloo +1

This paper presents a novel approach to one-class classifier fusion through locally adaptive learning with dynamic p-norm constraints. We introduce a framework that dynamical…

cs.RO2024

H-MaP: An Iterative and Hybrid Sequential Manipulation Planner

Berk Cicek, Arda Sarp Yenicesu, Cankut Bora Tuncer +2

This paper introduces H-MaP, a hybrid sequential manipulation planner that addresses complex tasks requiring both sequential actions and dynamic contact mode switches. Our approach…

cs.LG2024

CUER: Corrected Uniform Experience Replay for Off-Policy Continuous Deep Reinforcement Learning Algorithms

Arda Sarp Yenicesu, Furkan B. Mutlu, Suleyman S. Kozat +1

The utilization of the experience replay mechanism enables agents to effectively leverage their experiences on several occasions. In previous studies, the sampling probability of t…