Arash K. Ushani

Papers

Total Citations

568

H-Index

About

Arash K. Ushani is a robotics researcher whose work spans autonomous navigation, dynamic obstacle tracking, and human-robot interaction. His most impactful contribution is the "University of Michigan North Campus Long-Term Vision and Lidar Dataset" (2015), a landmark resource that has garnered over 548 citations. This dataset, collected using a Segway robot outfitted with omnidirectional cameras, 3D lidar, GPS, and proprioceptive sensors, provides a large-scale, long-term autonomy benchmark that has become a foundational tool for researchers in simultaneous localization and mapping (SLAM) and autonomous vehicle navigation. Ushani also advanced dynamic obstacle tracking with his 2015 work on continuous-time estimation, which simultaneously estimates an obstacle’s trajectory and shape from noisy, partial sensor data—a critical capability for safe autonomous driving. Earlier in his career, he explored human motor control in "Human Reach-to-Grasp Compensation with Object Pose Uncertainty" (2013), using a novel motion tracking framework to study how humans adapt grasping behavior under environmental uncertainty. Together, his contributions demonstrate a deep commitment to enabling robust perception and interaction in autonomous systems, from foundational datasets to real-time tracking algorithms.