Towards Urban Space Robots

Our three main focus points are: Elastic Collaboration of Edge IoTs for QoS Optimization, Space Intelligence Evolution with Autonomic Preference Learning, and Placeness Inference using Urban Physical and Social Data. Each Research direction is contributing to building an Intelligent Urban Space Robot.

We use an integrated approach to solving problems, and our international team consists of specialists with different competencies. Specifically we work interdisciplinary by inviting students from diverse backgrounds in computer science, data science, urban planning, and many more. Every team regularly shares the progress and direction in their research field to inspire other members with fresh ideas to finding solutions.

We are working with multiple Servers that are divided among the teams to compute their AI workloads. We also work with a large number of Raspberry Pis, NVIDIA Jetson devices of different generations, and many other low-end machines. We have two real-world test-beds set up around our campus to evaluate different research outcomes.

We are have a very international mindset and work together in teams. We support each other and have frequent contact with out professor through meetings or discussions about our research. Everyone is working hard and passionately to achieve goals related to research and funding projects.