  Tomographic imaging systems are expected to work with a wide range of samples
that house complex structures and challenging material compositions, which can
influence image quality in a bad way. Complex samples increase total
measurement duration and may introduce beam-hardening artifacts that lead to
poor reconstruction image quality. This work presents an online trajectory
optimization method for an X-ray computed tomography system with a robotic
sample holder. The proposed method reduces measurement time and increases
reconstruction image quality by generating an optimized spherical trajectory
for the given sample without prior knowledge. The trajectory is generated
successively at runtime based on intermediate sample measurements. We present
experimental results with the robotic sample holder where two sample
measurements using an optimized spherical trajectory achieve improved
reconstruction quality compared to a conventional spherical trajectory. Our
results demonstrate the ability of our system to increase reconstruction image
quality and avoid artifacts at runtime when no prior information about the
sample is provided.
