47 citations · 48 across the 6 of their papers we have counts for
9 papers
Multimodal Control of Manipulators: Coupling Kinematics and Vision for Self-Driving Laboratory Operations
Shifa Sulaiman, Amarnath H, Simon Bogh +1
Motion planning schemes are used for planning motions of a manipulator from an initial pose to a final pose during a task execution. A motion planning scheme generally comprises of…
GIFT: Geometry-Induced Functional Transfer for Category-level Object Manipulation
Cristiana de Farias, Luis Figueredo, Riddhiman Laha +5
Robotic manipulation of unfamiliar objects in new environments is challenging due to limited generalisation capabilities. We propose a new skill transfer framework, GIFT (Geometry-…
Haptic-guided assisted telemanipulation approach for grasping desired objects from heaps
Maxime Adjigble, Rustam Stolkin, Naresh Marturi
This paper presents an assisted telemanipulation framework for reaching and grasping desired objects from clutter. Specifically, the developed system allows an operator to select a…
Local Region-to-Region Mapping-based Approach to Classify Articulated Objects
Ayush Aggarwal, Rustam Stolkin, Naresh Marturi
Autonomous robots operating in real-world environments encounter a variety of objects that can be both rigid and articulated in nature. Having knowledge of these specific object pr…
3D Spectral Domain Registration-Based Visual Servoing
Maxime Adjigble, Brahim Tamadazte, Cristiana de Farias +2
This paper presents a spectral domain registration-based visual servoing scheme that works on 3D point clouds. Specifically, we propose a 3D model/point cloud alignment method, whi…
Grasp Transfer for Deformable Objects by Functional Map Correspondence
Cristiana de Farias, Brahim Tamadazte, Rustam Stolkin +1
Handling object deformations for robotic grasping is still a major problem to solve. In this paper, we propose an efficient learning-free solution for this problem where generated…
SpectGRASP: Robotic Grasping by Spectral Correlation
Maxime Adjigble, Cristiana de Farias, Rustam Stolkin +1
This paper presents a spectral correlation-based method (SpectGRASP) for robotic grasping of arbitrarily shaped, unknown objects. Given a point cloud of an object, SpectGRASP extra…
Dual Quaternion-Based Visual Servoing for Grasping Moving Objects
Cristiana de Farias, Maxime Adjigble, Brahim Tamadazte +2
This paper presents a new dual quaternion-based formulation for pose-based visual servoing. Extending our previous work on local contact moment (LoCoMo) based grasp planning, we de…
Simultaneous Tactile Exploration and Grasp Refinement for Unknown Objects
Cristiana de Farias, Naresh Marturi, Rustam Stolkin +1
This paper addresses the problem of simultaneously exploring an unknown object to model its shape, using tactile sensors on robotic fingers, while also improving finger placement t…