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Volodymyr Shcherbyna

5 accepted papers

2025

Arena 4.0: a Comprehensive Ros2 Development and Benchmarking Platform for Human-Centric Navigation Using Generative-Model-Based Environment Generation

ICRA 2025

Building upon the foundations laid by our previous work, this paper introduces Arena 4.0, a significant advancement of Arena 3.0 [1], Arena-Bench [2], Arena 1.0 [3], and Arena 2.0 [4]. Arena 4.0 provides three main novel contributions: 1) a generative-model-based world and scenario generation approa

Cited by 12SourceScholar
2025

Arena-Bench 2.0: A Comprehensive Benchmark of Social Navigation Approaches in Collaborative Environments

IROS 2025

Social navigation has become increasingly important for robots operating in human environments, yet many newly proposed navigation methods remain narrowly tailored or exist only as proof-of-concept prototypes. Building on our previous work with Arena, a social navigation development platform, we now

Cited by 0SourceScholar
2025

Demonstrating Arena 5.0: A Photorealistic ROS2 Simulation Framework for Developing and Benchmarking Social Navigation

RSS 2025poster

Building upon the foundations laid by our previous work, this paper introducesArena 5.0, the fifth iteration of our framework for robotics social navigation development and benchmarking. Arena 5.0 provides three main contributions: 1) The complete integration of NVIDIA Isaac Gym, enabling photoreali…

Cited by 0PDFScholar
2023

Arena-Rosnav 2.0: A Development and Benchmarking Platform for Robot Navigation in Highly Dynamic Environments

IROS 2023

Following up on our previous works, in this paper, we present Arena-Rosnav 2.0 an extension to our previous works Arena-Bench [1] and Arena-Rosnav [2], which adds a variety of additional modules for developing and benchmarking robotic navigation approaches. The platform is fundamentally restructured

Cited by 11SourcecodeScholar
2023

Demonstrating Arena-Web: A Web-based Development and Benchmarking Platform for Autonomous Navigation Approaches

RSS 2023poster

In recent years, mobile robot navigation approaches have become increasingly important due to various application areas ranging from healthcare to warehouse logistics. In particular, Deep Reinforcement Learning approaches have gained popularity for robot navigation but are not easily accessible to n…

Cited by 3SourcePDFScholar