M. Elbanhawi - Academia.edu (original) (raw)

Papers by M. Elbanhawi

Research paper thumbnail of Continuous-curvature bounded trajectory planning using parametric splines

This paper investigates trajectory generation for curvature continuous paths. A car-like wheeled ... more This paper investigates trajectory generation for curvature continuous paths. A car-like wheeled robot platform is considered. Planning is performed using a single B-spline curve that maintains continuity through the path. Constraints such as bounded curvature, velocity, and acceleration limits are considered. We minimize the traversal time while maintaining continuity and obeying the robot's constraints. Simulation experiments were successfully conducted to verify the efficiency and robustness of this approach.

Research paper thumbnail of Continuous Path Smoothing for Car-Like Robots Using B-Spline Curves

Journal of Intelligent & Robotic Systems, 2015

A practical approach for generating motion paths with continuous steering for car-like mobile rob... more A practical approach for generating motion paths with continuous steering for car-like mobile robots is presented here. This paper addresses two key issues in robot motion planning; path continuity and maximum curvature constraint for nonholonomic robots. The advantage of this new method is that it allows robots to account for their constraints in an efficient manner that facilitates real-time planning. Bspline curves are leveraged for their robustness and practical synthesis to model the vehicle's path. Comparative navigational-based analyses are presented to selected appropriate curve and nominate its parameters. Path continuity is achieved by utilizing a single path, to represent the trajectory, with no limitations on path, or orientation. The path parameters are formulated with respect to the robot's constraints. Maximum curvature is satisfied locally, in every segment using a smoothing algorithm, if needed. It is demonstrated that any local modifications of single sections have minimal effect on the entire path. Rigorous simulations are presented, to highlight the benefits of the proposed method, in comparison to existing approaches with regards to continuity, curvature control, path length and resulting acceleration. Experimental results validate that our approach mimics human steering with high accuracy. Accordingly, efficiently formulated continuous paths ultimately contribute towards passenger comfort improvement. Using presented approach, autonomous vehicles generate and follow paths that humans are accustomed to, with minimum disturbances.

Research paper thumbnail of Sampling-Based Robot Motion Planning: A Review

IEEE Access, 2014

Motion planning is a fundamental research area in robotics. Sampling-based methods offer an effic... more Motion planning is a fundamental research area in robotics. Sampling-based methods offer an efficient solution for what is otherwise a rather challenging dilemma of path planning. Consequently, these methods have been extended further away from basic robot planning into further difficult scenarios and diverse applications. A comprehensive survey of the growing body of work in sampling-based planning is given here. Simulations are executed to evaluate some of the proposed planners and highlight some of the implementation details that are often left unspecified. An emphasis is placed on contemporary research directions in this field. We address planners that tackle current issues in robotics. For instance, real-life kinodynamic planning, optimal planning, replanning in dynamic environments, and planning under uncertainty are discussed. The aim of this paper is to survey the state of the art in motion planning and to assess selected planners, examine implementation details and above all shed a light on the current challenges in motion planning and the promising approaches that will potentially overcome those problems.

Research paper thumbnail of i IEEE AccessTM Editorial Board xii IEEE AccessTM Associate Editors 1 A Contract-Based Methodology for Aircraft Electric Power System Design by P. Nuzzo, H. Xu, N. Ozay, JB Finn, AL Sangiovanni-Vincentelli, RM Murray, A. Donzé, and SA Seshia

Research paper thumbnail of Autonomous robots path planning: An adaptive roadmap approach

Developing algorithms that allow robots to independently navigate unknown environments is a widel... more Developing algorithms that allow robots to independently navigate unknown environments is a widely researched area of robotics. The potential for autonomous mobile robots use, in industrial and military applications, is boundless. Path planning entails computing a collision free path from a robot's current position to a desired target. The problem of path planning for these robots remains underdeveloped. Computational complexity, path optimization and robustness are some of the issues that arise. Current algorithms do not generate general solutions for different situations and require user experience and optimization. Classical algorithms are computationally extensive. This reduces the possibility of their use in real time applications. Additionally, classical algorithms do not allow for any control over attributes of the generated path. A new roadmap path planning algorithm is proposed in this paper. This method generates waypoints, through which the robot can avoid obstacles and reach its goal. At the heart of this algorithm is a method to control the distance of the waypoints from obstacles, without increasing its computational complexity. Several simulations were run to illustrate the robustness and adaptability of this approach, compared to the most commonly used path planning methods.

Research paper thumbnail of Continuous-curvature bounded trajectory planning using parametric splines

This paper investigates trajectory generation for curvature continuous paths. A car-like wheeled ... more This paper investigates trajectory generation for curvature continuous paths. A car-like wheeled robot platform is considered. Planning is performed using a single B-spline curve that maintains continuity through the path. Constraints such as bounded curvature, velocity, and acceleration limits are considered. We minimize the traversal time while maintaining continuity and obeying the robot's constraints. Simulation experiments were successfully conducted to verify the efficiency and robustness of this approach.

Research paper thumbnail of Continuous Path Smoothing for Car-Like Robots Using B-Spline Curves

Journal of Intelligent & Robotic Systems, 2015

A practical approach for generating motion paths with continuous steering for car-like mobile rob... more A practical approach for generating motion paths with continuous steering for car-like mobile robots is presented here. This paper addresses two key issues in robot motion planning; path continuity and maximum curvature constraint for nonholonomic robots. The advantage of this new method is that it allows robots to account for their constraints in an efficient manner that facilitates real-time planning. Bspline curves are leveraged for their robustness and practical synthesis to model the vehicle's path. Comparative navigational-based analyses are presented to selected appropriate curve and nominate its parameters. Path continuity is achieved by utilizing a single path, to represent the trajectory, with no limitations on path, or orientation. The path parameters are formulated with respect to the robot's constraints. Maximum curvature is satisfied locally, in every segment using a smoothing algorithm, if needed. It is demonstrated that any local modifications of single sections have minimal effect on the entire path. Rigorous simulations are presented, to highlight the benefits of the proposed method, in comparison to existing approaches with regards to continuity, curvature control, path length and resulting acceleration. Experimental results validate that our approach mimics human steering with high accuracy. Accordingly, efficiently formulated continuous paths ultimately contribute towards passenger comfort improvement. Using presented approach, autonomous vehicles generate and follow paths that humans are accustomed to, with minimum disturbances.

Research paper thumbnail of Sampling-Based Robot Motion Planning: A Review

IEEE Access, 2014

Motion planning is a fundamental research area in robotics. Sampling-based methods offer an effic... more Motion planning is a fundamental research area in robotics. Sampling-based methods offer an efficient solution for what is otherwise a rather challenging dilemma of path planning. Consequently, these methods have been extended further away from basic robot planning into further difficult scenarios and diverse applications. A comprehensive survey of the growing body of work in sampling-based planning is given here. Simulations are executed to evaluate some of the proposed planners and highlight some of the implementation details that are often left unspecified. An emphasis is placed on contemporary research directions in this field. We address planners that tackle current issues in robotics. For instance, real-life kinodynamic planning, optimal planning, replanning in dynamic environments, and planning under uncertainty are discussed. The aim of this paper is to survey the state of the art in motion planning and to assess selected planners, examine implementation details and above all shed a light on the current challenges in motion planning and the promising approaches that will potentially overcome those problems.

Research paper thumbnail of i IEEE AccessTM Editorial Board xii IEEE AccessTM Associate Editors 1 A Contract-Based Methodology for Aircraft Electric Power System Design by P. Nuzzo, H. Xu, N. Ozay, JB Finn, AL Sangiovanni-Vincentelli, RM Murray, A. Donzé, and SA Seshia

Research paper thumbnail of Autonomous robots path planning: An adaptive roadmap approach

Developing algorithms that allow robots to independently navigate unknown environments is a widel... more Developing algorithms that allow robots to independently navigate unknown environments is a widely researched area of robotics. The potential for autonomous mobile robots use, in industrial and military applications, is boundless. Path planning entails computing a collision free path from a robot's current position to a desired target. The problem of path planning for these robots remains underdeveloped. Computational complexity, path optimization and robustness are some of the issues that arise. Current algorithms do not generate general solutions for different situations and require user experience and optimization. Classical algorithms are computationally extensive. This reduces the possibility of their use in real time applications. Additionally, classical algorithms do not allow for any control over attributes of the generated path. A new roadmap path planning algorithm is proposed in this paper. This method generates waypoints, through which the robot can avoid obstacles and reach its goal. At the heart of this algorithm is a method to control the distance of the waypoints from obstacles, without increasing its computational complexity. Several simulations were run to illustrate the robustness and adaptability of this approach, compared to the most commonly used path planning methods.