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Christian Tirtawardhana

3 accepted papers

2022

Retro-RL: Reinforcing Nominal Controller With Deep Reinforcement Learning for Tilting-Rotor Drones

RA-L 2022

Studies that broaden drone applications into complex tasks require a stable control framework. Recently, deep reinforcement learning (RL) algorithms have been exploited in many studies for robot control to accomplish complex tasks. Unfortunately, deep RL algorithms might not be suitable for being de

Cited by 13SourceScholar
2021

CAROS-Q: Climbing Aerial RObot System Adopting Rotor Offset With a Quasi-Decoupling Controller

RA-L 2021

Unmanned Aerial Vehicles (UAVs) have continually proven their effectiveness in various fields. However, UAVs have not yet matured enough to be used for vertical surface maintenance tasks, such as building inspection or cleaning. To mitigate this issue, this letter proposes a novel design for a coaxi

Cited by 20SourceScholar
2020

Development and Analysis of Digging and Soil Removing Mechanisms for Mole-Bot: Bio-Inspired Mole-Like Drilling Robot

IROS 2020

Interests in exploration of new energy resources are increasing due to the exhaustion of existing resources. To explore new energy sources, various studies have been conducted to improve the drilling performance of drilling equipment for deep and strong ground. However, with better performance, the

Cited by 22SourceScholar