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Mojtaba Karimi

8 accepted papers

2022

PourNet: Robust Robotic Pouring Through Curriculum and Curiosity-based Reinforcement Learning

IROS 2022poster

Pouring liquids accurately into containers is one of the most challenging tasks for robots as they are unaware of the complex fluid dynamics and the behavior of liquids when pouring. Therefore, it is not possible to formulate a generic pouring policy for real-time applications. In this paper, we pro…

Cited by 10SourcecodeScholar
2022

RO-LOAM: 3D Reference Object-based Trajectory and Map Optimization in LiDAR Odometry and Mapping

RA-L 2022

We propose an extension to the LiDAR Odometry and Mapping framework (LOAM) that enables reference object-based trajectory and map optimization. Our approach assumes that the location and geometry of a large reference object are known, e.g., as a CAD model from Building Information Modeling (BIM) or

Cited by 10SourceScholar
2022

Skill-CPD: Real-time Skill Refinement for Shared Autonomy in Manipulator Teleoperation

IROS 2022

Advanced wireless communication networks provide lower latency and a higher transmission rate. Although this is an enabler for many new teleoperation applications, the risk of network instability or packet drop is still unavoidable. Real-time manipulator teleoperation requires data transmission with

Cited by 8SourcecodeScholar
2021

LoLa-SLAM: Low-Latency LiDAR SLAM Using Continuous Scan Slicing

RA-L 2021

Real-time 6D pose estimation is a key component for autonomous indoor navigation of Unmanned Aerial Vehicles (UAVs). This letter presents a low-latency LiDAR SLAM framework based on LiDAR scan slicing and concurrent matching, called LoLa-SLAM. Our framework uses sliced point cloud data from a rotati

Cited by 50SourceScholar
2021

NMPC-MP: Real-time Nonlinear Model Predictive Control for Safe Motion Planning in Manipulator Teleoperation

IROS 2021poster

Motion control and planning for the manipulator are critical components in manipulator teleoperation. Online (real-time) motion control is challenging for active obstacle avoidance and often results in fluctuating and unsafe motion. Offline motion planning, on the other hand, generates precise and s…

Cited by 20SourceScholar
2021

R-LOAM: Improving LiDAR Odometry and Mapping With Point-to-Mesh Features of a Known 3D Reference Object

RA-L 2021

LiDAR-based odometry and mapping is used in many robotic applications to retrieve the robot's position in an unknown environment and allows for autonomous operation in GPS-denied (e.g., indoor) environments. With a 3D LiDAR sensor, highly accurate localization becomes possible, which enables high qu

Cited by 52SourceScholar
2018

Delay Compensation for a Telepresence System With 3D 360 Degree Vision Based on Deep Head Motion Prediction and Dynamic FoV Adaptation

RA-L 2018

The usability of telepresence applications is strongly affected by the communication delay between the user and the remote system. Special attention needs to be paid in case the distant scene is experienced by means of a Head Mounted Display. A high motion-to-photon latency, which describes the time

Cited by 12SourceScholar
2018

Learning-Based Modular Task-Oriented Grasp Stability Assessment

IROS 2018poster

Assessing grasp stability is essential to prevent the failure of robotic manipulation tasks due to sensory data and object uncertainties. Learning-based approaches are widely deployed to infer the success of a grasp. Typically, the underlying model used to estimate the grasp stability is trained for…

Cited by 8SourceScholar