7 papers
Video2STL: Grounding VLM-Generated Temporal Specifications for Robot Learning
Merve Atasever, Keyan Azbijari, Cagan Bakirci +6
Video-based policy learning is particularly promising, as it illustrates target behaviors without requiring action annotations or embodiment-matched demonstrations. A central chall…
From LLM-Generated Specifications to Learned Quadruped Locomotion
Merve Atasever, Keyan Azbijari, Cagan Bakirci +5
Quadruped robot locomotion policies are often trained using reinforcement learning, which in turn relies heavily on hand-crafted reward functions. Designing reward functions requir…
Learning Gait-Aware Quadruped Locomotion with Temporal Logic Specifications
Merve Atasever, Cagan Bakirci, Alfredo Reina Corona +3
Reinforcement learning (RL) for quadruped locomotion commonly depends on fixed, hand-crafted, and Markovian reward functions that may limit interpretability of learned policies and…
Benchmarking Autonomous Driving Planners Across Leaderboards: A Unified CARLA-Based Evaluation
Merve Atasever, Alfredo Reina Corona, Zhuochen Liu +5
Autonomous driving remains a highly active research domain that seeks to enable vehicles to perceive dynamic environments, predict the future trajectories of traffic agents such as…
Multi-Agent Path Finding via Offline RL and LLM Collaboration
Merve Atasever, Matthew Hong, Mihir Nitin Kulkarni +2
Multi-Agent Path Finding (MAPF) poses a significant and challenging problem critical for applications in robotics and logistics, particularly due to its combinatorial complexity an…
Coordinating Spinal and Limb Dynamics for Enhanced Sprawling Robot Mobility
Merve Atasever, Ali Okhovat, Azhang Nazaripouya +4
Sprawling locomotion in vertebrates, particularly salamanders, demonstrates how body undulation and spinal mobility enhance stability, maneuverability, and adaptability across comp…
Motion Planning for Automata-based Objectives using Efficient Gradient-based Methods
Anand Balakrishnan, Merve Atasever, Jyotirmoy V. Deshmukh
In recent years, there has been increasing interest in using formal methods-based techniques to safely achieve temporal tasks, such as timed sequence of goals, or patrolling object…