Arun Narenthiran Sivakumar — accepted AI-conference papers

2024

Demonstrating CropFollow++: Robust Under-Canopy Navigation with Keypoints

Arun Narenthiran Sivakumar, Mateus Valverde Gasparino, Michael McGuire, Vitor Akihiro Hisano Higuti, M. Ugur Akcal, Girish Chowdhary

RSS 2024poster

We present an empirically robust vision-based navigation system for under-canopy agricultural robots using semantic keypoints. Autonomous under-canopy navigation is challenging due to the tight spacing between the crop rows (∼ 0.75 m), degradation in RTK-GPS accuracy due to multipath error, and nois…

Cited by 3 Source ↗PDF ↗Scholar ↗

2024

W-RIZZ: A Weakly-Supervised Framework for Relative Traversability Estimation in Mobile Robotics

Andre Schreiber, Arun Narenthiran Sivakumar, Peter Du, Mateus Valverde Gasparino, Girish Chowdhary, Katherine Rose Driggs-Campbell

RA-L 2024

Successful deployment of mobile robots in unstructured domains requires an understanding of the environment and terrain to avoid hazardous areas, getting stuck, and colliding with obstacles. Traversability estimation–which predicts where in the environment a robot can travel–is one prominent approac

Cited by 6 Source ↗code ↗Scholar ↗

2022

Proactive Anomaly Detection for Robot Navigation With Multi-Sensor Fusion

Tianchen Ji, Arun Narenthiran Sivakumar, Girish Chowdhary, Katherine Driggs-Campbell

RA-L 2022

Despite the rapid advancement of navigation algorithms, mobile robots often produce anomalous behaviors that can lead to navigation failures. The ability to detect such anomalous behaviors is a key component in modern robots to achieve high-levels of autonomy. Reactive anomaly detection methods iden

Cited by 69 Source ↗code ↗Scholar ↗

2022

WayFAST: Navigation With Predictive Traversability in the Field

Mateus Valverde Gasparino, Arun Narenthiran Sivakumar, Yixiao Liu, Andres E. Baquero Velasquez, Vitor A. H. Higuti, John G. Rogers +2

RA-L 2022

We present a self-supervised approach for learning to predict traversable paths for wheeled mobile robots that require good traction to navigate. Our algorithm, termed WayFAST (Waypoint Free Autonomous Systems for Traversability), uses RGB and depth data, along with navigation experience, to autonom

Cited by 73 Source ↗code ↗Scholar ↗

2021

Learned Visual Navigation for Under-Canopy Agricultural Robots

Arun Narenthiran Sivakumar, Sahil Modi, Mateus Valverde Gasparino, Che Ellis, Andres Eduardo Baquero Velasquez, Girish Chowdhary +1

RSS 2021poster

This paper describes a system for visually guided autonomous navigation of under-canopy farm robots. Low-cost under-canopy robots can drive between crop rows under the plant canopy and accomplish tasks that are infeasible for over-the-canopy drones or larger agricultural equipment. However; autonomo…

Cited by 76 Source ↗PDF ↗Scholar ↗