6 citations · 13 across the 14 of their papers we have counts for
14 papers · 1 filter
Learning to Throw Objects Safely in Multi-Obstacle Environments
Mohammadreza Kasaei, Klemen Voncina, Hamidreza Kasaei
Robotic throwing enables fast and efficient object placement beyond the robot's immediate workspace, but reliable throwing in cluttered environments remains underexplored. Existing…
Geometry-Aware Visual Odometry for Bronchoscopic Navigation via High-Gain Observer Fusion
Mohammadreza Kasaei, Francis Xiatian Zhang, Feng Li +3
Navigational bronchoscopy is critical for pulmonary interventions, yet current platforms depend heavily on pre-operative CT or external sensors, limiting their use in critical care…
Shape-Aware Whole-Body Control for Continuum Robots with Application in Endoluminal Surgical Robotics
Mohammadreza Kasaei, Mostafa Ghobadi, Mohsen Khadem
This paper presents a shape-aware whole-body control framework for tendon-driven continuum robots with direct application to endoluminal surgical navigation. Endoluminal procedures…
A Synergistic Framework for Learning Shape Estimation and Shape-Aware Whole-Body Control Policy for Continuum Robots
Mohammadreza Kasaei, Farshid Alambeigi, Mohsen Khadem
In this paper, we present a novel synergistic framework for learning shape estimation and a shape-aware whole-body control policy for tendon-driven continuum robots. Our approach l…
VITAL: Interactive Few-Shot Imitation Learning via Visual Human-in-the-Loop Corrections
Hamidreza Kasaei, Mohammadreza Kasaei
Imitation Learning (IL) has emerged as a powerful approach in robotics, allowing robots to acquire new skills by mimicking human actions. Despite its potential, the data collection…
Harnessing the Synergy between Pushing, Grasping, and Throwing to Enhance Object Manipulation in Cluttered Scenarios
Hamidreza Kasaei, Mohammadreza Kasaei
In this work, we delve into the intricate synergy among non-prehensile actions like pushing, and prehensile actions such as grasping and throwing, within the domain of robotic mani…
Language-guided Robot Grasping: CLIP-based Referring Grasp Synthesis in Clutter
Georgios Tziafas, Yucheng Xu, Arushi Goel +3
Robots operating in human-centric environments require the integration of visual grounding and grasping capabilities to effectively manipulate objects based on user instructions. T…
Learning Fine Pinch-Grasp Skills using Tactile Sensing from A Few Real-world Demonstrations
Xiaofeng Mao, Yucheng Xu, Ruoshi Wen +5
Imitation learning for robot dexterous manipulation, especially with a real robot setup, typically requires a large number of demonstrations. In this paper, we present a data-effic…
Instance-wise Grasp Synthesis for Robotic Grasping
Yucheng Xu, Mohammadreza Kasaei, Hamidreza Kasaei +1
Generating high-quality instance-wise grasp configurations provides critical information of how to grasp specific objects in a multi-object environment and is of high importance fo…
Agile and Versatile Robot Locomotion via Kernel-based Residual Learning
Milo Carroll, Zhaocheng Liu, Mohammadreza Kasaei +1
This work developed a kernel-based residual learning framework for quadrupedal robotic locomotion. Initially, a kernel neural network is trained with data collected from an MPC con…
Throwing Objects into A Moving Basket While Avoiding Obstacles
Hamidreza Kasaei, Mohammadreza Kasaei
The capabilities of a robot will be increased significantly by exploiting throwing behavior. In particular, throwing will enable robots to rapidly place the object into the target…
Robust and Dexterous Dual-arm Tele-Cooperation using Adaptable Impedance Control
Keyhan Kouhkiloui Babarahmati, Mohammadreza Kasaei, Carlo Tiseo +2
In recent years, the need for robots to transition from isolated industrial tasks to shared environments, including human-robot collaboration and teleoperation, has become increasi…
Simultaneous Multi-View Object Recognition and Grasping in Open-Ended Domains
Hamidreza Kasaei, Sha Luo, Remo Sasso +1
To aid humans in everyday tasks, robots need to know which objects exist in the scene, where they are, and how to grasp and manipulate them in different situations. Therefore, obje…
MVGrasp: Real-Time Multi-View 3D Object Grasping in Highly Cluttered Environments
Hamidreza Kasaei, Mohammadreza Kasaei
Nowadays robots play an increasingly important role in our daily life. In human-centered environments, robots often encounter piles of objects, packed items, or isolated objects. T…