# Image-Based Trajectory Tracking through Unknown Environments without Absolute Positioning

arXiv: https://arxiv.org/abs/2103.00055 · HTML: https://mlsanity.com/paper/2103.00055/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Feb 2021.

## Built on by (most cited first, 1 of 1)

- [Difference-Based Relational Learning for Zero-Shot Object-Goal Visual Navigation With Direct Sim-to-Real Transfer](https://mlsanity.com/paper/2607.15642/) (2026)

## Abstract (arXiv)

This paper describes a stereo image-based visual servoing system for trajectory tracking by a non-holonomic robot without externally derived pose information nor a known visual map of the environment. It is called trajectory servoing. The critical component is a feature-based, indirect Simultaneous Localization And Mapping (SLAM) method to provide a pool of available features with estimated depth, so that they may be propagated forward in time to generate image feature trajectories for visual servoing. Short and long distance experiments show the benefits of trajectory servoing for navigating unknown areas without absolute positioning. Empirically, trajectory servoing has better trajectory tracking performance than pose-based feedback when both rely on the same underlying SLAM system.