Search Results for author: Rustam Stolkin

Found 13 papers, 2 papers with code

Human operator cognitive availability aware Mixed-Initiative control

1 code implementation26 Aug 2021 Giannis Petousakis, Manolis Chiou, Grigoris Nikolaou, Rustam Stolkin

The controller leverages a state-of-the-art computer vision method and an off-the-shelf web camera to infer the cognitive availability of the operator and inform the AI-initiated LOA switching.

Disaster Response

Robust and fast generation of top and side grasps for unknown objects

no code implementations18 Jul 2019 Brice Denoun, Beatriz Leon, Claudio Zito, Rustam Stolkin, Lorenzo Jamone, Miles Hansard

In this work, we present a geometry-based grasping algorithm that is capable of efficiently generating both top and side grasps for unknown objects, using a single view RGB-D camera, and of selecting the most promising one.

2D Linear Time-Variant Controller for Human's Intention Detection for Reach-to-Grasp Trajectories in Novel Scenes

no code implementations19 Jun 2019 Claudio Zito, Tomasz Deregowski, Rustam Stolkin

Our approach also reduce the number of controllable dimensions for the user by providing only control on x- and y-axis, while orientation of the end-effector and the pose of its fingers are inferred by the system.

Let's Push Things Forward: A Survey on Robot Pushing

no code implementations13 May 2019 Jochen Stüber, Claudio Zito, Rustam Stolkin

In doing so, we dedicate a separate section to deep learning approaches which have seen a recent upsurge in the literature.

Hypothesis-based Belief Planning for Dexterous Grasping

no code implementations13 Mar 2019 Claudio Zito, Valerio Ortenzi, Maxime Adjigble, Marek Kopicki, Rustam Stolkin, Jeremy L. Wyatt

However, this planning approach was tried successfully only on simplified control problems.

Sensors, SLAM and Long-term Autonomy: A Review

no code implementations4 Jul 2018 Mubariz Zaffar, Shoaib Ehsan, Rustam Stolkin, Klaus McDonald Maier

Simultaneous Localization and Mapping, commonly known as SLAM, has been an active research area in the field of Robotics over the past three decades.

Simultaneous Localization and Mapping

Learning monocular visual odometry with dense 3D mapping from dense 3D flow

no code implementations6 Mar 2018 Cheng Zhao, Li Sun, Pulak Purkait, Tom Duckett, Rustam Stolkin

Dense 2D flow and a depth image are generated from monocular images by sub-networks, which are then used by a 3D flow associated layer in the L-VO network to generate dense 3D flow.

Monocular Visual Odometry

Dense RGB-D semantic mapping with Pixel-Voxel neural network

no code implementations30 Sep 2017 Cheng Zhao, Li Sun, Pulak Purkait, Rustam Stolkin

For intelligent robotics applications, extending 3D mapping to 3D semantic mapping enables robots to, not only localize themselves with respect to the scene's geometrical features but also simultaneously understand the higher level meaning of the scene contexts.

3D Reconstruction Scene Understanding +1

Single-Shot Clothing Category Recognition in Free-Configurations with Application to Autonomous Clothes Sorting

no code implementations22 Jul 2017 Li Sun, Gerardo Aragon-Camarasa, Simon Rogers, Rustam Stolkin, J. Paul Siebert

Our visual feature is robust to deformable shapes and our approach is able to recognise the category of unknown clothing in unconstrained and random configurations.

Weakly-supervised DCNN for RGB-D Object Recognition in Real-World Applications Which Lack Large-scale Annotated Training Data

1 code implementation19 Mar 2017 Li Sun, Cheng Zhao, Rustam Stolkin

We also propose a novel way to pretrain a DCNN for the depth modality, by training on virtual depth images projected from CAD models.

Object Recognition

A fully end-to-end deep learning approach for real-time simultaneous 3D reconstruction and material recognition

no code implementations14 Mar 2017 Cheng Zhao, Li Sun, Rustam Stolkin

We present the results of experiments, in which we trained our system to perform real-time 3D semantic reconstruction for 23 different materials in a real-world application.

3D Reconstruction Material Recognition

Cannot find the paper you are looking for? You can Submit a new open access paper.