https://scholar.dgist.ac.kr/handle/20.500.11750/101 2026-04-05T12:36:39Z https://scholar.dgist.ac.kr/handle/20.500.11750/59967 Title: Poster: How to Send Large Data in ROS 2 Author(s): Lee, Sanghoon; Kim, Taehun; Chae, Jiyeong; Park, Kyung-Joon Abstract: High-resolution data streams-such as images, Li-DAR point-clouds-are common in robotic communication, yet Robot Operating System 2 (ROS 2) struggles to transmit these streams due to increased average latency. On lossy wireless links, the default DDS communication stack in ROS 2 suffers significant performance degradation. This paper presents the first comprehensive network-layer analysis of ROS 2's DDS stack operating over wireless links with large payloads. We analyze three network bottlenecks that emerge during large-payload data transfers and presents DDS-level optimizations for each one. The proposed solutions are exposed through an XML-based QoS configuration interface, allowing them to be easily tuned. Experiments demonstrate that our approach transmits large-payload data successfully while maintaining lower latency than existing methods. 2025-09-22T15:00:00Z https://scholar.dgist.ac.kr/handle/20.500.11750/59902 Title: An Analytical Latency Model of the Data Distribution Service in ROS 2 Author(s): Park, Hyung-Seok; Lee, Sanghoon; Um, Doo-Sik; Ryu, Hyunho; Park, Kyung-Joon Abstract: After its initial release in 2007, the robot operating system (ROS) has been widely adopted as an open-source robotics middleware suite. In 2017, ROS 2 is introduced to offer enhanced performance, and it has since become the de facto standard for robot software development. In this paper, we propose an analytical latency model for the data distribution service (DDS) in ROS 2. DDS operates at the application layer on top of the user datagram protocol (UDP). In ROS 2, retransmissions for reliable data delivery are handled at the application layer, resulting in latency characteristics different from those of the transmission control protocol (TCP). We derive a closed-form analytical model to characterize the latency of DDS reliable data delivery in ROS 2, taking into account key parameters such as the packet delivery ratio, the data period, and the heartbeat period in DDS. Our extensive empirical study shows that the proposed model matches well with the empirical data, with an average error of 6.88 % across 35 different scenarios. 2025-05-19T15:00:00Z https://scholar.dgist.ac.kr/handle/20.500.11750/59335 Title: DIDoS: Disturbance-induced Denial-of-service Attack in Networked Cyber-physical Systems Author(s): Kim, Sangjun; Lee, Sanghoon; Park, Kyung-Joon Abstract: Event-triggered control (ETC) in a cyber-physical system (CPS) is an efficient aperiodic control strategy that generates control packets only when a control-triggering condition is satisfied. However, the CPS with ETC introduces a new point of vulnerability. A well-designed disturbance signal can unnecessarily trigger control events and the resulting excessive packet exchanges can destabilize the physical systems due to network saturation. In this paper, we propose a novel CPS attack vector entitled the disturbance-induced denial of service (DIDoS) attack, which has the following key characteristics: DIDoS cannot be mitigated by a conventional network security method such as a firewall. Unlike most cyber-physical attacks, DIDoS does not require knowledge of physical system dynamics. Under DIDoS, a disturbance signal into a single physical system can saturate the whole network and destabilize all the physical systems connected to the network. We study the relationship between the network delay and the stability of physical systems under DIDoS. We derive a stability condition under a time-varying network delay and quantitatively describe network saturation under DIDoS with an IEEE 802.11 wireless network model. Our simulation results show that DIDoS can saturate the network and destabilize all the physical systems. 2025-10-31T15:00:00Z https://scholar.dgist.ac.kr/handle/20.500.11750/59333 Title: Time-aware Costmap for Smoother and Less Disruptive AMR Navigation With ROS 2 Author(s): Chae, Jiyeong; Seo, Hyunkyo; Lee, Sanghoon; Park, Kyung-Joon Abstract: Autonomous mobile robots (AMRs) are increasingly deployed in industrial settings, where they perform various tasks that replace human labor, thereby boosting operational efficiency. In such smart manufacturing environments where multiple types of robots coexist, effective management of dynamic obstacles during AMR navigation is crucial. However, the standard ROS 2 navigation stack lacks built-in mechanisms specifically to handle dynamic obstacles. Many existing studies on dynamic obstacle avoidance are limited to local path planning, focusing primarily on real-time recognition and evasion based on sensor data. In this paper, we propose a time-aware costmap framework that leverages information about areas frequently occupied by dynamic obstacles, integrating it into the global costmap to enable smoother and less-disruptive navigation. The framework not only enhances AMR stability but also increases productivity in industrial environments. The time-aware costmap framework offers three key advantages: First, it enables the global planner to select routes that are smooth and minimally disruptive. Second, it integrates a custom layer featuring time-bound dynamic obstacles into the global costmap as a plugin, enabling seamless adaptation within existing navigation frameworks. Finally, it works effectively using only a 2D LiDAR sensor, minimizing hardware and software overhead. We validate the performance of the proposed framework in a Gazebo simulation environment modeled after a milk-run distribution system. The results demonstrate that the framework substantially improves safety and stability by lowering curvature, jerk, and collision risks. While this comes with a trade-off of about 20% lower throughput due to smoother detours, the framework’s emphasis on smoothness and safety offers greater practical value for reliable navigation in industrial environments. 2025-11-30T15:00:00Z