activity
20242026
collaborators

6 papers

cs.RO2026

A Terrain-Adaptive epsilon-Constraint MPC for Uneven Terrain Kinodynamic Planning

Otobong Jerome, Geesara Kalathunga, Tiago Nascimento

Kinodynamic planning for car-like vehicles on uneven terrain requires simultaneously optimizing competing objectives such as path efficiency and pose stability. This work presents…

cs.CV2026

Mapping the Unseen: Unified Promptable Panoptic Mapping with Dynamic Labeling using Foundation Models

Mohamad Al Mdfaa, Raghad Salameh, Geesara Kulathunga +2

Panoptic maps enable robots to reason about both geometry and semantics. However, open-vocabulary models repeatedly produce closely related labels that split panoptic entities and…

cs.RO2025

A Real-Time Framework for Intermediate Map Construction and Kinematically Feasible Off-Road Planning Without OSM

Otobong Jerome, Geesara Prathap Kulathunga, Devitt Dmitry +2

Off-road environments present unique challenges for autonomous navigation due to their complex and unstructured nature. Traditional global path-planning methods, which typically ai…

cs.RO2025

On Kinodynamic Global Planning in a Simplicial Complex Environment: A Mixed Integer Approach

Otobong Jerome, Alexandr Klimchik, Alexander Maloletov +1

This work casts the kinodynamic planning problem for car-like vehicles as an optimization task to compute a minimum-time trajectory and its associated velocity profile, subject to…

cs.RO2025

A Genetic Approach to Gradient-Free Kinodynamic Planning in Uneven Terrains

Otobong Jerome, Alexandr Klimchik, Alexander Maloletov +1

This paper proposes a genetic algorithm-based kinodynamic planning algorithm (GAKD) for car-like vehicles navigating uneven terrains modeled as triangular meshes. The algorithm's d…

cs.RO2024

Resilient Timed Elastic Band Planner for Collision-Free Navigation in Unknown Environments

Geesara Kulathunga, Abdurrahman Yilmaz, Zhuoling Huang +6

In autonomous navigation, trajectory replanning, refinement, and control command generation are essential for effective motion planning. This paper presents a resilient approach to…