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Rooholla Khorrambakht

6 accepted papers

2026

WorldPlanner: Monte Carlo Tree Search and MPC with Action-Conditioned Visual World Models

Rooholla Khorrambakht, Joaquim Ortiz-Haro, Joseph Amigo, Omar Mostafa, Daniel Dugas, Franziska Meier +1
ICRA 2026poster

Robots must understand their environment from raw sensory inputs and reason about the consequences of their actions in it to solve complex tasks. Behavior Cloning (BC) leverages task-specific human demonstrations to learn this knowledge as end-to-end policies. However, these policies are difficult t…

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2025

First Order Model-Based RL through Decoupled Backpropagation

Joseph Amigo, Rooholla Khorrambakht, Elliot Chane-Sane, Nicolas Mansard, Ludovic Righetti
CoRL 2025poster

There is growing interest in reinforcement learning (RL) methods that leverage the simulator's derivatives to improve learning efficiency. While early gradient-based approaches have demonstrated superior performance compared to derivative-free methods, accessing simulator gradients is often impracti…

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2024

DiffOcclusion: Differentiable Optimization Based Control Barrier Functions for Occlusion-Free Visual Servoing

Shiqing Wei, Bolun Dai, Rooholla Khorrambakht, Prashanth Krishnamurthy, Farshad Khorrami
RA-L 2024

The visibility (possibly partial) of some image features is crucial to a broad class of visual servoing-based control. In this letter, we consider the setting of image-based visual servoing (IBVS) and address the fundamental problem of keeping a moving object with an unknown motion profile in the fi

Cited by 21Source ↗Scholar ↗
2024

Sailing Through Point Clouds: Safe Navigation Using Point Cloud Based Control Barrier Functions

Bolun Dai, Rooholla Khorrambakht, Prashanth Krishnamurthy, Farshad Khorrami
RA-L 2024

The capability to navigate safely in an unstructured environment is crucial when deploying robotic systems in real-world scenarios. Recently, control barrier function (CBF) based approaches have been highly effective in synthesizing safety-critical controllers. In this letter, we propose a novel CBF

Cited by 11Source ↗Scholar ↗
2023

Safe Navigation and Obstacle Avoidance Using Differentiable Optimization Based Control Barrier Functions

Bolun Dai, Rooholla Khorrambakht, Prashanth Krishnamurthy, Vinicius Mariano Gonçalves, Anthony Tzes, Farshad Khorrami
RA-L 2023

Control barrier functions (CBFs) have been widely applied to safety-critical robotic applications. However, the construction of control barrier functions for robotic systems remains a challenging task. Recently, collision detection using differentiable optimization has provided a way to compute the

Cited by 52Source ↗Scholar ↗
2022

Kinematics-Inertial Fusion for Localization of a 4-Cable Underactuated Suspended Robot Considering Cable Sag

Eren Allak, Rooholla Khorrambakht, Christian Brommer, Stephan Weiss
IROS 2022poster

Suspended Cable-Driven Parallel Robots (SCDPR) have intriguing capabilities on large scales but still have open challenges in precisely estimating the end-effector pose. The cables exhibit a downward curved shape, also known as cable sag which needs to be accounted for in the pose estimation. The ca…

Cited by 5Source ↗Scholar ↗