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Albertus Hendrawan Adiwahono

4 accepted papers

2025

Multi-Robot Reliable Navigation in Uncertain Topological Environments With Graph Attention Networks

Zhuoyuan Yu, Hongliang Guo, Chee-Meng Chew, Albertus Hendrawan Adiwahono, Jianle Chan, Brina Shong Wey Tynn +1
RA-L 2025

This paper studies the multi-robot reliable navigation problem in uncertain topological networks, which aims at maximizing the robot team's on-time arrival probabilities in the face of road network uncertainties. The uncertainty in these networks stems from the unknown edge traversability, which is

Cited by 2Source ↗code ↗Scholar ↗
2021

State Estimation for Hybrid Wheeled-Legged Robots Performing Mobile Manipulation Tasks

Yangwei You, Samuel Cheong, Tai Pang Chen, Yuda Chen, Kun Zhang, Cihan Acar +3
ICRA 2021poster

This paper introduces a general state estimation framework fusing multiple sensor information for hybrid wheeled-legged robots performing mobile manipulation tasks. At the core of the state estimator is a novel unified odometry for hybrid locomotion which can seamlessly maintain tracking and has no…

Cited by 12Source ↗Scholar ↗
2020

Towards More Possibilities: Motion Planning and Control for Hybrid Locomotion of Wheeled-Legged Robots

Jingyuan Sun, Yangwei You, Xuran Zhao, Albertus Hendrawan Adiwahono, Chee-Meng Chew
RA-L 2020

This letter proposed a control framework to tackle the hybrid locomotion problem of wheeled-legged robots. It comes as a hierarchical structure with three layers: hybrid foot placement planning, Centre of Mass (CoM) trajectory optimization and whole-body control. General mathematical representation

Cited by 26Source ↗Scholar ↗
2019

Sparse-3D Lidar Outdoor Map-Based Autonomous Vehicle Localization

Syed Zeeshan Ahmed, Vincensius Billy Saputra, Saurab Verma, Kun Zhang, Albertus Hendrawan Adiwahono
IROS 2019poster

Difficulties in capturing unique structures in the outdoor environment hinders the map-based Autonomous Vehicles (AV) localization performance. Accordingly, this necessitates the use of high resolution sensors to capture more information from the environment. However, this approach is costly and lim…

Cited by 19Source ↗Scholar ↗