About

Amin Fakhari is an Assistant Professor of Practice at the Department of Mechanical Engineering at Stony Brook University. He holds a Ph.D. from Isfahan University of Technology, obtained in 2015. His research focuses on robotics, dynamical systems, control systems, and mechatronics. His work involves developing and applying advanced techniques in these areas to solve engineering problems, contributing to the fields of automation and intelligent systems within mechanical engineering.

Research topics

• Computer Science
• Artificial Intelligence
• Physics
• Computer vision
• Engineering
• Classical mechanics
• Structural engineering
• Simulation
• Mathematics
• Algorithm
• Mechanical engineering

Selected publications

• Trajectory Optimization for Self-Wrap-Aware Cable-Towed Planar Object Manipulation under Implicit Tension Constraints

  arXiv (Cornell University) · 2026-03-10

  preprintOpen access

  Cable/rope elements are pervasive in deformable-object manipulation, often serving as a deformable force-transmission medium whose routing and contact determine how wrenches are delivered. In cable-towed manipulation, transmission is unilateral and hybrid: the tether can pull only when taut and becomes force-free when slack; in practice, the tether may also contact the object boundary and self-wrap around edges, which is not merely collision avoidance but a change of the wrench transmission channel by shifting the effective application point and moment arm, thereby coupling routing geometry with rigid-body motion and tensioning. We formulate self-wrap towing as a routing-aware, tensioning-implicit trajectory optimization (TITO) problem that couples (i) a tensioning-implicit taut/slack constraint and (ii) routing-conditioned transmission maps for effective length and wrench, and we build a relaxation hierarchy from a strict mode-conditioned reference to three tractable relaxations: Full-Mode Relaxation (FMR), Binary-Mode Relaxation (BMR), and Implicit-Mode Relaxation (IMR). Across planar towing tasks, we find that making routing an explicit decision often yields conservative solutions that stay near switching boundaries, whereas IMR induces self-wrap through state evolution and exploits the redirected torque channel whenever turning requires it.

  PublisherDOI

• Trajectory Optimization for Self-Wrap-Aware Cable-Towed Planar Object Manipulation under Implicit Tension Constraints

  ArXiv.org · 2026-03-10

  articleOpen access

  Cable/rope elements are pervasive in deformable-object manipulation, often serving as a deformable force-transmission medium whose routing and contact determine how wrenches are delivered. In cable-towed manipulation, transmission is unilateral and hybrid: the tether can pull only when taut and becomes force-free when slack; in practice, the tether may also contact the object boundary and self-wrap around edges, which is not merely collision avoidance but a change of the wrench transmission channel by shifting the effective application point and moment arm, thereby coupling routing geometry with rigid-body motion and tensioning. We formulate self-wrap towing as a routing-aware, tensioning-implicit trajectory optimization (TITO) problem that couples (i) a tensioning-implicit taut/slack constraint and (ii) routing-conditioned transmission maps for effective length and wrench, and we build a relaxation hierarchy from a strict mode-conditioned reference to three tractable relaxations: Full-Mode Relaxation (FMR), Binary-Mode Relaxation (BMR), and Implicit-Mode Relaxation (IMR). Across planar towing tasks, we find that making routing an explicit decision often yields conservative solutions that stay near switching boundaries, whereas IMR induces self-wrap through state evolution and exploits the redirected torque channel whenever turning requires it.

  PublisherOA PDF

• Motion Planning for Object Manipulation by Edge-Rolling

  arXiv (Cornell University) · 2024-10-11

  preprintOpen accessSenior author

  A common way to manipulate heavy objects is to maintain at least one point of the object in contact with the environment during the manipulation. When the object has a cylindrical shape or, in general, a curved edge, not only sliding and pivoting motions but also rolling the object along the edge can effectively satisfy this condition. Edge-rolling offers several advantages in terms of efficiency and maneuverability. This paper aims to develop a novel approach for approximating the prehensile edge-rolling motion on any path by a sequence of constant screw displacements, leveraging the principles of screw theory. Based on this approach, we proposed an algorithmic method for task-space-based path generation of object manipulation between two given configurations using a sequence of rolling and pivoting motions. The method is based on an optimization algorithm that takes into account the joint limitations of the robot. To validate our approach, we conducted experiments to manipulate a cylinder along linear and curved paths using the Franka Emika Panda manipulator.

  PublisherOA PDFDOI

• Motion Planning for Object Manipulation by Edge-Rolling

  2024-10-14

  articleSenior author

  A common way to manipulate heavy objects is to maintain at least one point of the object in contact with the environment during the manipulation. When the object has a cylindrical shape or, in general, a curved edge, not only sliding and pivoting motions but also rolling the object along the edge can effectively satisfy this condition. Edge-rolling offers several advantages in terms of efficiency and maneuverability. This paper aims to develop a novel approach for approximating the prehensile edge-rolling motion on any path by a sequence of constant screw displacements, leveraging the principles of screw theory. Based on this approach, we proposed an algorithmic method for task-space-based path generation of object manipulation between two given configurations using a sequence of rolling and pivoting motions. The method is based on an optimization algorithm that takes into account the joint limitations of the robot. To validate our approach, we conducted experiments to manipulate a cylinder along linear and curved paths using the Franka Emika Panda manipulator.Video— https://youtu.be/MX1-MAR9ubc

  PublisherDOI

• Propagation of Error and Uncertainty in a Computer-Assisted Orthopedic Surgical System

  IEEE Transactions on Instrumentation and Measurement · 2024-01-01 · 3 citations

  article

  Computer Assisted Orthopedic Surgical Systems (CAOSS) require accurate estimation of the relative position/ orientation of points and surface on the bone to reproduce the preoperative resection plan accurately, such as the osteotomy lines for resection. This position/orientation is determined by a series of measurements ranging from bone registration, system calibration, and real-time tracking. Thus, the error and uncertainty of position/orientation in each measurement step would propagate to and accumulate the uncertainty of the final stage for resection. In this paper, an analytical method is proposed to calculate the propagation of errors and uncertainties in CAOSS. Furthermore, a method to illustrate the uncertainty of resection is introduced. An example using the proposed analytical method, based on a projection guidance system, is presented to illustrate the effect of tracking uncertainty of resection. The outcome of resection uncertainty is demonstrated as a hyperboloid with a 98 % confidence region. This is applied together with the tumor in computer display to check the possibility for the resection to intrude the tumor and fail the surgery, and to determine if the preoperative resection plan should be adjusted with a larger safety margin. The methodology of the propagation of error and uncertainty presented in this paper can facilitate surgeons to make better decisions of surgery by creating and monitoring the resection plan with the consideration of the accuracy of the system. Furthermore, the theoretical principle of uncertainty propagation can be applied to other systems that utilizes the 4×4 homogeneous transformation matrices.

  PublisherDOI

• Development of a Novel Impedance-Controlled Quasi-Direct-Drive Robotic Hand

  arXiv (Cornell University) · 2024-05-29 · 1 citations

  preprintOpen accessSenior author

  Most robotic hands and grippers rely on actuators with large gearboxes and force sensors for controlling gripping force. However, this might not be ideal for tasks that require the robot to interact with an unstructured and unknown environment. In this paper, we introduce a novel quasi-direct-drive two-fingered robotic hand with variable impedance control in the joint space and Cartesian space. The hand has a total of four degrees of freedom, backdrivable differential gear trains, and four brushless direct current (BLDC) motors. Motor torque is controlled through Field-Oriented Control (FOC) with current sensing. Variable impedance control enables the robotic hand to execute dexterous manipulation tasks safely during environment-robot and human-robot interactions. The quasi-direct-drive actuators eliminate the need for complex tactile/force sensors or precise motion planning when handling environmental contact. A majority-3D-printed assembly makes this a low-cost research platform built with affordable, readily available off-the-shelf components. Experimental validation demonstrates the robotic hand's capability for stable force-closure and form-closure grasps in the presence of disturbances, reliable in-hand manipulation, and safe dynamic manipulations despite contact with the environment.

  PublisherOA PDFDOI

• Experimental and Computational Study of Error and Uncertainty in Real-Time Camera-Based Tracking of a Two-Dimensional Marker for Orthopedic Surgical Navigation

  Journal of Verification Validation and Uncertainty Quantification · 2023 · 2 citations

  • Artificial Intelligence
  • Computer Science
  • Computer vision

  Abstract Tracking of the position and orientation of a moving object by a camera can be accomplished by attaching a 2D marker with a specific pattern on the object. Recently, we have developed a projection-based surgical navigation system that can accurately guide in real-time the pre-operative plan of resection in orthopedic surgery, such as joint replacement or wide-resection of osteosarcoma (bone tumor). To this end, it is important to study the accuracy of registration and tracking due to various sources of errors, such as the printing resolution and quality of the 2D marker. In this study, we investigate and provide analysis of error and uncertainty for real-time tracking using a 2D marker with a camera. Experiments and computational simulations were conducted to quantify the estimation of errors in position and orientation due to the printing error of 2D markers using a 600-dpi laser printer. In addition, a theory of uncertainty propagation in a form of congruence transformation was derived for such systems and is illustrated with experimental results.

  PublisherDOI

• Computing a Task-Dependent Grasp Metric Using Second-Order Cone Programs

  2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · 2021-09-27 · 4 citations

  article1st authorCorresponding

  Evaluating a grasp generated by a set of hand-object contact locations is a key component of many grasp planning algorithms. In this paper, we present a novel second-order cone program (SOCP) based optimization formulation for evaluating a grasps’ ability to apply wrenches to generate a linear motion along a given direction and/or an angular motion about the given direction. Our quality measure can be computed efficiently since the SOCP is a convex optimization problem, which can be solved optimally with interior point methods. A key feature of our approach is that we can consider the effect of contact wrenches from any contact of the object with the environment. This is different from the extant literature where only the effect of finger-object contacts is considered. Exploiting the environmental contact is useful in many manipulation scenarios either to enhance the dexterity of simple hands or improve the payload capability of the manipulator. In contrast to most existing approaches, our approach also takes into account the practical constraint that the maximum contact force that can be applied at a finger-object contact can be different for each contact. We can also include the effect of external forces like gravity, as well as the joint torque constraints of the fingers/manipulators. Furthermore, for a given motion path as a constant screw motion or a sequence of constant screw motions, we can discretize the path and compute a global grasp metric to accomplish the whole task with a chosen set of finger-object contact locations.

  PublisherDOI

• Motion and Force Planning for Manipulating Heavy Objects by Pivoting

  2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · 2021 · 7 citations

  1st authorCorresponding
  • Computer Science
  • Artificial Intelligence
  • Computer Science

  Manipulation of objects by exploiting their contact with the environment can enhance both the dexterity and payload capability of robotic manipulators. A common way to manipulate heavy objects beyond the payload capability of a robot is to use a sequence of pivoting motions, wherein, an object is moved while some contact points between the object and a support surface are kept fixed. The goal of this paper is to develop an algorithmic approach for automated plan generation for object manipulation with a sequence of pivoting motions. A plan for manipulating a heavy object consists of a sequence of joint angles of the manipulator, the corresponding object poses, as well as the joint torques required to move the object. The constraint of maintaining object contact with the ground during manipulation results in nonlinear constraints in the configuration space of the robot, which is challenging for motion planning algorithms. Exploiting the fact that pivoting motion corresponds to movements in a subgroup of the group of rigid body motions, SE(3), we present a novel task-space based planning approach for computing a motion plan for both the manipulator and the object while satisfying contact constraints. We also combine our motion planning algorithm with a grasping force synthesis algorithm to ensure that friction constraints at the contacts and actuator torque constraints are satisfied. We present simulation results with a dual-armed Baxter robot to demonstrate our approach.

  PublisherDOI

• Computing a Task-Dependent Grasp Metric Using Second Order Cone Programs

  arXiv (Cornell University) · 2021-04-25

  preprintOpen access1st authorCorresponding

  Evaluating a grasp generated by a set of hand-object contact locations is a key component of many grasp planning algorithms. In this paper, we present a novel second order cone program (SOCP) based optimization formulation for evaluating a grasps' ability to apply wrenches to generate a linear motion along a given direction and/or an angular motion about the given direction. Our quality measure can be computed efficiently, since the SOCP is a convex optimization problem, which can be solved optimally with interior point methods. A key feature of our approach is that we can consider the effect of contact wrenches from any contact of the object with the environment. This is different from the extant literature where only the effect of finger-object contacts is considered. Exploiting the environmental contact is useful in many manipulation scenarios either to enhance the dexterity of simple hands or improve the payload capability of the manipulator. In contrast to most existing approaches, our approach also takes into account the practical constraint that the maximum contact force that can be applied at a finger-object contact can be different for each contact. We can also include the effect of external forces like gravity, as well as the joint torque constraints of the fingers/manipulators. Furthermore, for a given motion path as a constant screw motion or a sequence of constant screw motions, we can discretize the path and compute a global grasp metric to accomplish the whole task with a chosen set of finger-object contact locations.

  PublisherOA PDFDOI

Frequent coauthors

• Imin Kao

  Stony Brook University

  9 shared

• Mehdi Keshmiri

  Isfahan University of Technology

  5 shared

• Aditya Patankar

  5 shared

• Nilanjan Chakraborty

  Stony Brook University

  3 shared

• Vahid Danesh

  2 shared

• Guangyu He

  Neusoft (China)

  2 shared

• Fazel Khan

  Stony Brook University Hospital

  2 shared

• Maede Boroji

  2 shared

Education

• PhD, Mechanical Engineering

  Isfahan University of Technology