Selected work

Representative Papers

Lights-Out: An Automated Ground Segment for unstaffed Satellite Operations

Oct 24, 2025

To address challenges in satellite ground segment operations—including unattended operation during off-hours, manual user experiment scheduling and monitoring, and delayed emergency response—this study proposes a periodic fully autonomous ground segment architecture. The architecture integrates automated task scheduling, automatic execution of flight operations procedures, intelligent system health monitoring, and configurable emergency response mechanisms to autonomously resolve conflicts between primary and user missions. It unifies telemetry, tracking, and command (TTC) systems with a user mission management platform, enabling remote RF equipment access and real-time browser-based data visualization. A self-service user portal with sub-second responsiveness is implemented. The architecture has been successfully deployed for the first time in the DLR Heinrich Hertz satellite mission, achieving 24/7 fully autonomous operations, minimum task response time under 60 seconds, and substantial improvements in mission flexibility and operational efficiency.

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CARGO: A Co-Optimization Framework for EV Charging and Routing in Goods Delivery Logistics

Aug 02, 2025

This work addresses the joint optimization of routing and charging strategies for electric delivery trucks under time-window constraints in urban logistics. We formulate a precise mixed-integer linear programming (MILP) model that simultaneously incorporates multi-dimensional charging constraints—including charger availability, charging cost, geographic distance, and real-time state-of-charge—while ensuring feasible route execution. To enhance computational scalability, we propose an efficient heuristic algorithm tailored to this integrated problem. Extensive experiments on real-world logistics data demonstrate that our approach reduces charging costs by 39% and 22% compared to the Earliest-Deadline-First (EDF) and Nearest-Distance-First (NDF) baselines, respectively, while maintaining equivalent task completion rates. To the best of our knowledge, this is the first framework to jointly optimize routing and charging under comprehensive, realistic charging infrastructure constraints. The results significantly improve both operational efficiency and economic viability of electric urban freight systems.

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Recent publications

Latest Papers

Lights-Out: An Automated Ground Segment for unstaffed Satellite Operations

Oct 24, 2025

To address challenges in satellite ground segment operations—including unattended operation during off-hours, manual user experiment scheduling and monitoring, and delayed emergency response—this study proposes a periodic fully autonomous ground segment architecture. The architecture integrates automated task scheduling, automatic execution of flight operations procedures, intelligent system health monitoring, and configurable emergency response mechanisms to autonomously resolve conflicts between primary and user missions. It unifies telemetry, tracking, and command (TTC) systems with a user mission management platform, enabling remote RF equipment access and real-time browser-based data visualization. A self-service user portal with sub-second responsiveness is implemented. The architecture has been successfully deployed for the first time in the DLR Heinrich Hertz satellite mission, achieving 24/7 fully autonomous operations, minimum task response time under 60 seconds, and substantial improvements in mission flexibility and operational efficiency.

0 citationsRead paper

CARGO: A Co-Optimization Framework for EV Charging and Routing in Goods Delivery Logistics

Aug 02, 2025

This work addresses the joint optimization of routing and charging strategies for electric delivery trucks under time-window constraints in urban logistics. We formulate a precise mixed-integer linear programming (MILP) model that simultaneously incorporates multi-dimensional charging constraints—including charger availability, charging cost, geographic distance, and real-time state-of-charge—while ensuring feasible route execution. To enhance computational scalability, we propose an efficient heuristic algorithm tailored to this integrated problem. Extensive experiments on real-world logistics data demonstrate that our approach reduces charging costs by 39% and 22% compared to the Earliest-Deadline-First (EDF) and Nearest-Distance-First (NDF) baselines, respectively, while maintaining equivalent task completion rates. To the best of our knowledge, this is the first framework to jointly optimize routing and charging under comprehensive, realistic charging infrastructure constraints. The results significantly improve both operational efficiency and economic viability of electric urban freight systems.

0 citationsRead paper