Eliezer Lozano

About

Eliezer Lozano is a leading researcher at the intersection of robotics, human perception, and immersive telepresence. His work focuses on a critical, emerging challenge: how to make a human feel truly present and comfortable when viewing the world through the eyes of a remote, autonomous robot. Lozano’s major contribution is the formalization of “human perception-optimized planning,” a new motion planning paradigm that prioritizes user comfort and naturalness over purely robotic efficiency. His most-cited paper (22 citations) introduces this concept, addressing the sickness and disorientation that often plague virtual reality telepresence. Through a series of studies (including work with 21 and 7 citations), he has systematically analyzed user preferences, demonstrating that smooth, predictable robot paths are significantly preferred over piecewise linear ones for a first-person VR experience. By defining what makes robot motion feel “natural” and “comfortable” from a human’s perspective, Lozano’s research is foundational for the future of remote work, exploration, and social interaction via telepresence robots.

Research Focus

Key Achievements

Top Papers

1. 1
   Human perception-optimized planning for comfortable VR-based telepresence

   22 citations · 2020
2. 2
   A visibility-based pursuit-evasion game between two nonholonomic robots in environments with obstacles

   21 citations · 2022
3. 3
   Comfort and sickness while virtually aboard an autonomous telepresence robot

   7 citations · 2021
4. 4
   Analysis of User Preferences for Robot Motions in Immersive Telepresence

   7 citations · 2021
5. 5
   Defining Preferred and Natural Robot Motions in Immersive Telepresence from a First-Person Perspective

   4 citations · 2021

Key Collaborators

Contact & Links