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Ashraf Elnagar

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12 papers

2 author rows

EAAI Journal 2025 Journal Article

Unlocking language boundaries: AraCLIP - transforming Arabic language and image understanding through cross-lingual models

Muhammad Al-Barham
Imad Afyouni
Khalid Almubarak
Ayad Turky
Ibrahim Abaker Targio Hashem
Ali Bou Nassif
Ismail Shahin
Ashraf Elnagar

In the domain of image retrieval, the integration of text and images has been transformative, facilitating models that transcend language barriers. This paper introduces Arabic Contrastive Language-Image Pre-training (AraCLIP), an extension of the Contrastive Language-Image Pre-training (CLIP) model tailored for Arabic image retrieval. AraCLIP leverages the CLIP architecture, introducing Knowledge Distillation to transfer cross-modal knowledge from a pre-trained English model to an Arabic counterpart. Unlike existing multilingual models lacking Arabic contextual nuances, AraCLIP addresses biases in image retrieval tasks. Our methodology involves dataset preparation, incorporating a synthetic dataset of about 12. 5M samples, which translated using a unique neural machine translation model for accurate English-to-Arabic translation. The training phase utilizes Knowledge Distillation, treating an English model as the teacher and a pre-trained Arabic model as the student. AraCLIP focuses on optimizing computational efficiency, maximizing cosine similarity, and minimizing Mean Squared Error. Our best model surpasses the state-of-the-art multilingual model by approximately 10% across various evaluation metrics, including Mean Reciprocal Rank (MRR) and Recall. In addition, it demonstrates competitive performance in ImageNet-based zero-shot classification tasks. We have also released several datasets to support text image-related tasks 1 1 https: //huggingface. co/Arabic-Clip. . AraCLIP along with published resources will leverage enhanced capabilities for Arabic image retrieval and opens avenues for diverse applications.

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ICRA Conference 2007 Conference Paper

A Practical Pursuit-Evasion Algorithm: Detection and Tracking

Amna AlDahak
Ashraf Elnagar

This paper presents a practical algorithm for evader detection and tracking using one or more pursuers. The solution employs two advanced data structures. The first one is the rapidly-exploring random tree (RRT). It is constructed randomly but evenly distributed to generate a roadmap that captures the connectivity of the free space. The second data structure is the k-dimensional tree (Kd-Tree). Upon completion of the RRTs construction, their vertices are inserted in a Kd-Tree. At the tracking phase, the Kd-Tree will be queried repeatedly for retrieving the set of potential locations to be used by each pursuer in order to monitor or track an evader. Thus, the usage of the Kd-Tree will reduce the querying cost, during tracking, to a logarithmic time. A lazy collision detection strategy is used to resolve collisions with obstacles at runtime. As a result unnecessary checks are eliminated and hence improving the system performance. Simulation results show the validity of the proposed algorithm.

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IROS Conference 2005 Conference Paper

A comparative study between visibility-based roadmap path planning algorithms

Leena Lulu
Ashraf Elnagar

The aim of this paper is to evaluate the performance of our proposed art gallery-based roadmap algorithm against well-known and frequently cited visibility-based motion planning algorithms: the visibility graph and the visibility-based probabilistic roadmap. The comparison involves several criteria among which are: the cardinality of the graph, the completeness of the algorithm, coverage and connectivity of the free configuration space (CS/sub free/) and computational cost. Our proposed algorithm is robust and fast as it generally covers the whole CS/sub free/, based on the well-known art gallery theorem. It efficiently seeks to construct a roadmap that contains the smallest possible number of nodes (called guards) as opposed to generating a large number of nodes when compared to other motion planning approaches. The simulation results demonstrate that our proposed algorithm outperforms both algorithms and proves to not only combine the attractive features of both algorithms but also eliminate the drawbacks of each one.

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IROS Conference 2005 Conference Paper

An art gallery-based approach to autonomous robot motion planning in global environments

Ashraf Elnagar
Leena Lulu

In this paper, we present a novel art gallery-based algorithm for placing a small number of guards to cover a global environment with obstacles for an autonomous robot. The guards are required to cover the entire workspace that is represented as a simple polygon with n vertices and h holes (obstacles). The proposed algorithm efficiently computes a (small) number of guards in simple polygons with holes, which runs in O (n log n) time and requires a linear storage complexity. However, an additional set of connection nodes is computed to form the connectivity graph, which contains all guards. This graph has far less number of vertices when compared to similar data structures used in conventional visibility-based or probabilistic-based motion planning algorithms. The resulting placement of guards and connectors can then be used as control points in the path of an autonomous mobile robot for navigation or inspection tasks. The proposed algorithm is not only offering a better performance in terms of computational cost but also an easy implementation. Simulation results demonstrate the efficiency, robustness, and potential of the proposed algorithm.

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ICRA Conference 2003 Conference Paper

An adaptive motion prediction model for trajectory planner systems

Ashraf Elnagar
Abdulla M. Hussein

In this paper, we describe an algorithm for predicting future positions and orientation of a moving object in a time-varying environment using an autoregressive model (ARM). No constraint is placed on the obstacles motion. The model addresses prediction of translational and rotational motions. Rotational motion is represented using quaternions rather than Euler representation to improve the algorithm performance and accuracy of the prediction results. Compared to other similar systems, the proposed algorithm has an adaptive capability, which enables it to predict over multiple time-steps rather than fixed ones as reported in other works. Such algorithm can be used in a variety of applications. An important one is its application in the framework of designing reliable navigational systems for autonomous mobile robots and more particularly in building effective trajectory planners. Simulation results show how significantly this model could reduce computational cost.

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IROS Conference 2002 Conference Paper

Motion planning using Maxwell's equations

Abdulla M. Hussein
Ashraf Elnagar

This paper presents a new formulation of the artificial potential approach to the motion planning problem for a mobile robot in a global environment. To model the potential (magnetic) field by Maxwell's Equations that completely eliminate the local minima problem, which is exhibited in most artificial potential methods, such as Harmonic functions based methods. However, the proposed model is superior to the Harmonic one because it is easily extendable to 3D, the time dimension is modeled by default which means it is a suitable model for time-varying environments, computations are less and hence faster, and most important it eliminates the "flat-regions" problem. In this work, electrical currents are assumed to be floating in a cluttered environment with obstacles. The obstacles are assigned zero conductivity whereas the goal point is assigned the highest electrical conductivity. The magnetic field induced by the electric currents is used to find a free path between the start and goal points. Simulation results reflects the validity and the potential of the proposed model.

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IROS Conference 1998 Conference Paper

Acceleration-based optimal trajectory planning in 3D environments

Ashraf Elnagar
Abdulla M. Hussein

An approach to generating acceleration-based optimal smooth piecewise trajectories is proposed. Given two configurations (position and orientation) in 3D, we search for the minimal energy trajectory that minimizes the integral of the squared acceleration, opposed to curvature, which is widely investigated. The variation in both components of acceleration controls the smoothness of generated trajectories. Our objective is to search for the trajectory along which a free moving robot is able to accelerate (decelerate) to a safe speed in an optimal way. A numerical iterative procedure is devised for computing the optimal piecewise trajectory as a solution of a constrained boundary value problem.

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ICRA Conference 1997 Conference Paper

On smooth and safe trajectory planning in 2D environments

Abdulla M. Hussein
Ashraf Elnagar

A novel approach to generating optimal smooth piecewise trajectories based on a new energy measure is proposed. Given the configurations (position and direction) of two points in the plane, we search for the minimal energy trajectory that minimizes the integral of the squared acceleration opposed to curvature, which has been the predominant energy measure studied in the literature. The smoothness of the optimal trajectory depends on how the tangential and normal components of acceleration vary over an interval of time. A numerical iterative procedure is devised for computing the optimal piecewise trajectory as a solution of a constrained boundary value problem. The resulting trajectories are not only smooth but also safe with optimal velocity (acceleration) profiles and therefore suitable for robot motion planning applications. The feasibility of the proposed approach is illustrated by several simulation examples. Besides motion planning, the resulting trajectories may be useful in computer graphics and geometric design.

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ICRA Conference 1995 Conference Paper

Robust Detection of Moving Objects by a Moving Observer on Planar Surfaces

Ashraf Elnagar
Anup Basu

We introduce a technique for detecting moving objects from an image sequence obtained with a moving camera using the planarity constraint. To increase the robustness of this technique, false motion caused by inaccuracies in sensor readings is eliminated by use of a morphological filter. This involves two successive operations-erosion and dilation-performed on a motion compensated image. Experimental results with real images are presented. Applications to the compression of moving images are now being investigated.

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ICRA Conference 1995 Conference Paper

Surface Integration for Inspection Tasks

Anup Basu
Ashraf Elnagar
Mark Fiala

In underwater environments it is often difficult to obtain a big/clear picture of a scene. For that reason, a system that can integrate small pieces of images (taken from close range) into a composite 3D surface, is developed here. The device, along with 3D position/orientation estimation equipment, can be used for inspection of hulls of ships anchored in a bay, or for examination of underwater pipes and tanks. Experimental results are presented which validate the algorithms developed.

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IROS Conference 1993 Conference Paper

Smooth and acceleration minimizing trajectories for mobile robots

Ashraf Elnagar
Anup Basu

An approach to generating smooth piecewise local trajectories for mobile robots is proposed. Given the configurations (position and direction) of two points, one searches for the trajectory that minimizes the integral of acceleration (tangential and normal). The resulting trajectory should not only be smooth but also safe in order to be applicable in real-life situations, so the authors investigate two different obstacle-avoidance constraints that satisfy the minimization problem. Unfortunately, in this case the problem becomes more complex and unsuitable for real-time implementations. Therefore, the authors introduce two simple solutions, based on the idea of polynomial fitting to generate safe trajectories, once a collision is detected with the original smooth trajectory. Simulation results for the different algorithms are presented.

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ICRA Conference 1992 Conference Paper

Heuristics for local path planning

Ashraf Elnagar
Anup Basu

The authors describe a heuristic technique for solving the problem of path planning based on local information for a mobile robot with acceleration constraints moving amidst a set of stationary obstacles. The concept of safety is introduced to design a planning strategy. A path which maximizes the product of safety based on local information and attraction towards the goal is chosen. The safety function depends on the acceleration bounds. The attraction toward the goal depends on the distance from the goal. Two additional heuristics are proposed to improve the efficiency of the search process and to enhance the ability of the robot to avoid obstacles. Some simulation examples of the algorithm corresponding to different navigational environments are discussed. >

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