Papers
2
Total Citations
10
H-Index
2
About
S. Schillo’s research bridges the critical intersection of autonomous systems and human-robot interaction, with a focus on last-mile delivery technologies and intelligent control. Their most-cited work, “A comparative review of user acceptance factors for drones and sidewalk robots in autonomous last mile delivery” (2025, 7 citations), provides a timely synthesis of how customer expectations and urban sustainability challenges shape the adoption of groundbreaking delivery robots. This review identifies key psychological and infrastructural barriers, offering a roadmap for designing more user-friendly autonomous logistics. In earlier work, Schillo developed a novel two-layer reinforcement learning approach for controlling a 2DOF manipulator (2010, 3 citations), demonstrating how on-policy temporal difference learning can manage highly nonlinear robotic systems by autonomously selecting joint torques. This contribution showcases a deep technical expertise in machine learning for robotics. Though a relatively early-career researcher, Schillo’s work is already informing both the engineering and social dimensions of autonomous mobility, making their research essential reading for those interested in the real-world deployment of robots in public spaces.
Research Focus
Key Achievements
Top Papers
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