Maxime Adjigble
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View article: Geometrically-Aware One-Shot Skill Transfer of Category-Level Objects
Geometrically-Aware One-Shot Skill Transfer of Category-Level Objects Open
Robotic manipulation of unfamiliar objects in new environments is challenging and requires extensive training or laborious pre-programming. We propose a new skill transfer framework, which enables a robot to transfer complex object manipul…
View article: Task-Informed Grasping of Partially Observed Objects
Task-Informed Grasping of Partially Observed Objects Open
In this letter, we address the problem of task-informed grasping in scenarios where only incomplete or partial object information is available. Existing methods, which either focus on task-Aware grasping or grasping under partiality, typic…
View article: Haptic-guided assisted telemanipulation approach for grasping desired objects from heaps
Haptic-guided assisted telemanipulation approach for grasping desired objects from heaps Open
This paper presents an assisted telemanipulation framework for reaching and grasping desired objects from clutter. Specifically, the developed system allows an operator to select an object from a cluttered heap and effortlessly grasp it, w…
View article: 3D Spectral Domain Registration-Based Visual Servoing
3D Spectral Domain Registration-Based Visual Servoing Open
International audience
View article: Asservissement visuel 3D direct dans le domaine spectral
Asservissement visuel 3D direct dans le domaine spectral Open
This paper presents a direct 3D visual servo scheme for the automatic alignment of point clouds (respectively, objects) using visual information in the spectral domain. Specifically, we propose an alignment method for 3D models/point cloud…
View article: 3D Spectral Domain Registration-Based Visual Servoing
3D Spectral Domain Registration-Based Visual Servoing Open
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, which works by finding a global transformation between referen…
View article: SpectGRASP: Robotic Grasping by Spectral Correlation
SpectGRASP: Robotic Grasping by Spectral Correlation Open
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 extracts contact points on the object's surface matching the han…
View article: Dual Quaternion-Based Visual Servoing for Grasping Moving Objects
Dual Quaternion-Based Visual Servoing for Grasping Moving Objects Open
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 demonstrate grasping of arbitrarily moving objects in 3D spac…
View article: Metrics and Benchmarks for Remote Shared Controllers in Industrial Applications
Metrics and Benchmarks for Remote Shared Controllers in Industrial Applications Open
Remote manipulation is emerging as one of the key robotics tasks needed in extreme environments. Several researchers have investigated how to add AI components into shared controllers to improve their reliability. Nonetheless, the impact o…
View article: Hypothesis-based Belief Planning for Dexterous Grasping
Hypothesis-based Belief Planning for Dexterous Grasping Open
Belief space planning is a viable alternative to formalise partially observable control problems and, in the recent years, its application to robot manipulation problems has grown. However, this planning approach was tried successfully onl…
View article: Dynamic grasp and trajectory planning for moving objects
Dynamic grasp and trajectory planning for moving objects Open
This paper shows how a robot arm can follow and grasp moving objects tracked by a vision system, as is needed when a human hands over an object to the robot during collaborative working. While the object is being arbitrarily moved by the h…
View article: One-shot learning and generation of dexterous grasps for novel objects
One-shot learning and generation of dexterous grasps for novel objects Open
This paper presents a method for one-shot learning of dexterous grasps and grasp generation for novel objects. A model of each grasp type is learned from a single kinesthetic demonstration and several types are taught. These models are use…