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Rohit Dhakate

3 accepted papers

2025

CaRoSaC: A Reinforcement Learning-Based Kinematic Control of Cable-Driven Parallel Robots by Addressing Cable Sag Through Simulation

RA-L 2025

This letter introduces the Cable Robot Simulation and Control (CaRoSaC) Framework, which integratesa realistic simulation environment with a model-free reinforcement learning control methodology for suspended Cable-Driven Parallel Robots (CDPRs), accounting for the effects of cable sag. Our approach

Cited by 2SourceScholar
2022

Autonomous Control of Redundant Hydraulic Manipulator Using Reinforcement Learning with Action Feedback

IROS 2022poster

This article presents an entirely data-driven approach for autonomous control of redundant manipulators with hydraulic actuation. The approach only requires minimal system information, which is inherited from a simulation model. The non-linear hydraulic actuation dynamics are modeled using actuator…

Cited by 7SourceScholar
2022

CNS Flight Stack for Reproducible, Customizable, and Fully Autonomous Applications

RA-L 2022

While low-level auto pilot stacks for aerial vehicles focus on robust control, sensing, and estimation, the continuous advancement of higher-level autonomy for aerial vehicles requires much more complex higher-level flight stacks in order to enable safe, fully autonomous long-duration missions. Rath

Cited by 4SourceScholar