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The DSpace digital repository system captures, stores, indexes, preserves, and distributes digital research material.Wed, 28 Feb 2024 16:57:54 GMT2024-02-28T16:57:54ZA Pragmatic Approach to Exploiting Full Force Capacity for Serial Redundant Manipulators
http://hdl.handle.net/10985/14555
A Pragmatic Approach to Exploiting Full Force Capacity for Serial Redundant Manipulators
BUSSON, David; BEAREE, Richard
Considering a set of robotic tasks which involve physical interaction with the environment, the theoretical knowledge of the full force capacity of the manipulator is a key factor in the design or development of an efficient and economically attractive solution. Carrying its own weight while countering forces may be too much for a robot in certain configurations. Kinematic redundancy with regard to a task allows a robot to perform it in a continuous space of articular configurations; space in which the payload of the robot may vary dramatically. It may be impossible to withstand a physical interaction in some configurations, while it may be easily sustainable in others that bring the end-effector to the same location. This becomes obviously more prevalent for a limited payload robot. This letter describes a framework for these kind of operations, in which kinematic redundancy is used to explore the full extent of a force capacity for a givenmanipulator and task (in this letter, the terms “force” and “wrench” may interchangeably refer to two-, three-, or six-dimensional forces depending on the dimension of the problem and on whether they may or may not include components of translational forces and/or moments. Their dimensional definition will be explicitly given whenever specifically needed). A pragmatic force capacity index (FCI) is proposed. The FCI offers a sound basis for redundancy resolution via optimization or complete redundancy exploration, and may provide good hints for end-effector design. A practical use case involving 7-DOFs KUKA LBR iiwa was used to demonstrate the relevance of the proposed method.
Mon, 01 Jan 2018 00:00:00 GMThttp://hdl.handle.net/10985/145552018-01-01T00:00:00ZBUSSON, DavidBEAREE, RichardConsidering a set of robotic tasks which involve physical interaction with the environment, the theoretical knowledge of the full force capacity of the manipulator is a key factor in the design or development of an efficient and economically attractive solution. Carrying its own weight while countering forces may be too much for a robot in certain configurations. Kinematic redundancy with regard to a task allows a robot to perform it in a continuous space of articular configurations; space in which the payload of the robot may vary dramatically. It may be impossible to withstand a physical interaction in some configurations, while it may be easily sustainable in others that bring the end-effector to the same location. This becomes obviously more prevalent for a limited payload robot. This letter describes a framework for these kind of operations, in which kinematic redundancy is used to explore the full extent of a force capacity for a givenmanipulator and task (in this letter, the terms “force” and “wrench” may interchangeably refer to two-, three-, or six-dimensional forces depending on the dimension of the problem and on whether they may or may not include components of translational forces and/or moments. Their dimensional definition will be explicitly given whenever specifically needed). A pragmatic force capacity index (FCI) is proposed. The FCI offers a sound basis for redundancy resolution via optimization or complete redundancy exploration, and may provide good hints for end-effector design. A practical use case involving 7-DOFs KUKA LBR iiwa was used to demonstrate the relevance of the proposed method.FIR Filter-Based Online Jerk-Controlled Trajectory Generation
http://hdl.handle.net/10985/11402
FIR Filter-Based Online Jerk-Controlled Trajectory Generation
BESSET, Pierre; BEAREE, Richard; GIBARU, Olivier
This paper presents a novel approach to generate online jerk-limited trajectories for multi-DOF robotic systems. Finite Impulse Response filters are used to efficiently turn low computational cost acceleration-limited profiles into jerk-limited profiles. Starting from a new setpoint, e.g. an event given by external sensors, and an arbitrary state of motion, i.e. with nonzero initial velocity and acceleration values, the proposed method can generate different shapes of jerk profile, including timeoptimal and fixed-time jerk-limited trajectories. A new definition of the velocity, acceleration and jerk kinematic limits can be instantaneously taken into account during the motion. Moreover, the very low calculation time (less than 1 microsecond) makes it possible to easily control a multi-DOF system during one control cycle (classically about 1 millisecond), while preserving time for other computer processing. The algorithm is experimentally tested on the new 7-DOF industrial robot KUKA LWR iiwa.
Fri, 01 Jan 2016 00:00:00 GMThttp://hdl.handle.net/10985/114022016-01-01T00:00:00ZBESSET, PierreBEAREE, RichardGIBARU, OlivierThis paper presents a novel approach to generate online jerk-limited trajectories for multi-DOF robotic systems. Finite Impulse Response filters are used to efficiently turn low computational cost acceleration-limited profiles into jerk-limited profiles. Starting from a new setpoint, e.g. an event given by external sensors, and an arbitrary state of motion, i.e. with nonzero initial velocity and acceleration values, the proposed method can generate different shapes of jerk profile, including timeoptimal and fixed-time jerk-limited trajectories. A new definition of the velocity, acceleration and jerk kinematic limits can be instantaneously taken into account during the motion. Moreover, the very low calculation time (less than 1 microsecond) makes it possible to easily control a multi-DOF system during one control cycle (classically about 1 millisecond), while preserving time for other computer processing. The algorithm is experimentally tested on the new 7-DOF industrial robot KUKA LWR iiwa.A Modified DLS Scheme With Controlled Cyclic Solution for Inverse Kinematics in Redundant Robots
http://hdl.handle.net/10985/21035
A Modified DLS Scheme With Controlled Cyclic Solution for Inverse Kinematics in Redundant Robots
SAFEEA; BEAREE, Richard; NETO, Pedro
Redundancy in robotic manipulators has many advantages. It is successfully used to achieve better dexterity, and to avoid obstacles, singularities, or the kinematic limitations. However, redundancy makes the inverse kinematics (IK) problem harder to solve. The damped least squares (DLS) is a powerful method for calculating the IK of redundant robots, but it suffers from noncyclicity issue, where a closed curve motion in the Cartesian space of the end-effector (EEF) does not map into a closed curve in the joint space. This results in nonrepetitive motion in the joint space, even though the EEF motion is repetitive. In this article, we present a solution for the noncyclicity problem in the DLS method. The proposed scheme was successfully tested both in simulation (9 DoF robot) and on a real robotic manipulator (7 DoF robot).
Fri, 01 Jan 2021 00:00:00 GMThttp://hdl.handle.net/10985/210352021-01-01T00:00:00ZSAFEEABEAREE, RichardNETO, PedroRedundancy in robotic manipulators has many advantages. It is successfully used to achieve better dexterity, and to avoid obstacles, singularities, or the kinematic limitations. However, redundancy makes the inverse kinematics (IK) problem harder to solve. The damped least squares (DLS) is a powerful method for calculating the IK of redundant robots, but it suffers from noncyclicity issue, where a closed curve motion in the Cartesian space of the end-effector (EEF) does not map into a closed curve in the joint space. This results in nonrepetitive motion in the joint space, even though the EEF motion is repetitive. In this article, we present a solution for the noncyclicity problem in the DLS method. The proposed scheme was successfully tested both in simulation (9 DoF robot) and on a real robotic manipulator (7 DoF robot).Improving the Accuracy of Industrial Robots by offline Compensation of Joints Errors
http://hdl.handle.net/10985/7745
Improving the Accuracy of Industrial Robots by offline Compensation of Joints Errors
OLABI, Adel; DAMAK, Mohamed; BEAREE, Richard; GIBARU, Olivier; LELEU, Stéphane
The use of industrial robots in many fields of industry like prototyping, pre-machining and end milling is limited because of their poor accuracy. Robot joints are mainly responsible for this poor accuracy. The flexibility of robots joints and the kinematic errors in the transmission systems produce a significant error of position in the level of the end-effector. This paper presents these two types of joint errors. Identification methods are presented with experimental validation on a 6 axes industrial robot, STAUBLI RX 170 BH. An offline correction method used to improve the accuracy of this robot is validated experimentally.
Tue, 01 Jan 2013 00:00:00 GMThttp://hdl.handle.net/10985/77452013-01-01T00:00:00ZOLABI, AdelDAMAK, MohamedBEAREE, RichardGIBARU, OlivierLELEU, StéphaneThe use of industrial robots in many fields of industry like prototyping, pre-machining and end milling is limited because of their poor accuracy. Robot joints are mainly responsible for this poor accuracy. The flexibility of robots joints and the kinematic errors in the transmission systems produce a significant error of position in the level of the end-effector. This paper presents these two types of joint errors. Identification methods are presented with experimental validation on a 6 axes industrial robot, STAUBLI RX 170 BH. An offline correction method used to improve the accuracy of this robot is validated experimentally.Efficient Calculation of Minimum Distance Between Capsules and Its Use in Robotics
http://hdl.handle.net/10985/14515
Efficient Calculation of Minimum Distance Between Capsules and Its Use in Robotics
SAFEEA, Mohammad; NETO, Pedro; BEAREE, Richard
The problem of minimum distance calculation between line-segments/capsules, in 3D space, is an important subject in many engineering applications, spanning CAD design, computer graphics, simulation, and robotics. In the latter, the human robot minimum distance is the main input for collision avoidance/detection algorithms to measure collision imminence. Capsules can be used to represent humans and objects, including robots, in a given dynamic environment. In this scenario, it is important to calculate the minimum distance between capsules ef ciently, especially for scenes (situations) that include a high number of capsules. This paper investigates the utilization of QR factorization for performing ef cient minimum distance calculation between capsules. The problem is reformulated as a bounded variable optimization in which an af ne transformation, deduced from QR factorization, is applied on the region of feasible solutions. A geometrical approach is proposed to calculate the solution, which is achieved by computing the point closest to the origin from the transferred region of feasible solutions. This paper is concluded with numerical tests, showing that the proposed method compares favorably with the most ef cient method reported in the literature.
Mon, 01 Jan 2018 00:00:00 GMThttp://hdl.handle.net/10985/145152018-01-01T00:00:00ZSAFEEA, MohammadNETO, PedroBEAREE, RichardThe problem of minimum distance calculation between line-segments/capsules, in 3D space, is an important subject in many engineering applications, spanning CAD design, computer graphics, simulation, and robotics. In the latter, the human robot minimum distance is the main input for collision avoidance/detection algorithms to measure collision imminence. Capsules can be used to represent humans and objects, including robots, in a given dynamic environment. In this scenario, it is important to calculate the minimum distance between capsules ef ciently, especially for scenes (situations) that include a high number of capsules. This paper investigates the utilization of QR factorization for performing ef cient minimum distance calculation between capsules. The problem is reformulated as a bounded variable optimization in which an af ne transformation, deduced from QR factorization, is applied on the region of feasible solutions. A geometrical approach is proposed to calculate the solution, which is achieved by computing the point closest to the origin from the transferred region of feasible solutions. This paper is concluded with numerical tests, showing that the proposed method compares favorably with the most ef cient method reported in the literature.Reducing the Computational Complexity of Mass-Matrix Calculation for High DOF Robots
http://hdl.handle.net/10985/17376
Reducing the Computational Complexity of Mass-Matrix Calculation for High DOF Robots
SAFEEA, Mohammad; BEAREE, Richard; NETO, Pedro
Increasingly, robots have more degrees of freedom (DOF), imposing a need for calculating more complex dynamics. As a result, better efficiency in carrying out dynamics computations is becoming more important. In this study, an efficient method for computing the joint space inertia matrix (JSIM) for high DOF serially linked robots is addressed. We call this method the Geometric Dynamics Algorithm for High number of robot Joints (GDAHJ). GDAHJ is non-symbolic, preserve simple formulation, and it is convenient for numerical implementation. This is achieved by simplifying the way to recursively derive the mass-matrix exploiting the unique property of each column of the JSIM and minimizing the number of operations with O(n2) complexity. Results compare favorably with existing methods, achieving better performance over state-of-the-art by Featherstone when applied for robots with more than 13 DOF.
Mon, 01 Jan 2018 00:00:00 GMThttp://hdl.handle.net/10985/173762018-01-01T00:00:00ZSAFEEA, MohammadBEAREE, RichardNETO, PedroIncreasingly, robots have more degrees of freedom (DOF), imposing a need for calculating more complex dynamics. As a result, better efficiency in carrying out dynamics computations is becoming more important. In this study, an efficient method for computing the joint space inertia matrix (JSIM) for high DOF serially linked robots is addressed. We call this method the Geometric Dynamics Algorithm for High number of robot Joints (GDAHJ). GDAHJ is non-symbolic, preserve simple formulation, and it is convenient for numerical implementation. This is achieved by simplifying the way to recursively derive the mass-matrix exploiting the unique property of each column of the JSIM and minimizing the number of operations with O(n2) complexity. Results compare favorably with existing methods, achieving better performance over state-of-the-art by Featherstone when applied for robots with more than 13 DOF.Task-oriented rigidity optimization for 7 DOF redundant manipulators
http://hdl.handle.net/10985/17377
Task-oriented rigidity optimization for 7 DOF redundant manipulators
BUSSON, David; BEAREE, Richard; OLABI, Adel
In this work, redundancy resolution has been employed to increase the Cartesian mechanical rigidity of 7 DOF robot manipulators during tasks requiring stiff interactions with the environment (e.g. milling or drilling). The Cartesian static stiffness of the end-effector for a given joint configuration is deduced from an identified joints stiffness model. The Cartesian reflected rigidity evolution over an analytically computed self-motion of the manipulator shows significant variations that clearly highlight the need to select the right set of joint angles among the possible ones. A global optimization scheme of the redundant DOF is proposed to determine the stiffest robot configurations for a given pose of the end-effector. An experimental study on 7 DOF KUKA LBR iiwa then shows the relevance of the proposed approach in finding the redundant robot joint angles that optimize this rigidity criteria.
Sun, 01 Jan 2017 00:00:00 GMThttp://hdl.handle.net/10985/173772017-01-01T00:00:00ZBUSSON, DavidBEAREE, RichardOLABI, AdelIn this work, redundancy resolution has been employed to increase the Cartesian mechanical rigidity of 7 DOF robot manipulators during tasks requiring stiff interactions with the environment (e.g. milling or drilling). The Cartesian static stiffness of the end-effector for a given joint configuration is deduced from an identified joints stiffness model. The Cartesian reflected rigidity evolution over an analytically computed self-motion of the manipulator shows significant variations that clearly highlight the need to select the right set of joint angles among the possible ones. A global optimization scheme of the redundant DOF is proposed to determine the stiffest robot configurations for a given pose of the end-effector. An experimental study on 7 DOF KUKA LBR iiwa then shows the relevance of the proposed approach in finding the redundant robot joint angles that optimize this rigidity criteria.Collision Avoidance of Redundant Robotic Manipulators Using Newton’s Method
http://hdl.handle.net/10985/18196
Collision Avoidance of Redundant Robotic Manipulators Using Newton’s Method
SAFEEA, Mohammad; BEAREE, Richard; NETO, Pedro
This study investigates the application of Newton method to the problems of collision avoidance and path planning for robotic manipulators, especially robots with high Degrees of Freedom (DOF). The proposed algorithm applies to the potential fields method, where the Newton technique is used for performing the optimization. As compared to classical gradient descent method this implementation is mathematically elegant, enhances the performance of motion generation, eliminates oscillations, does not require gains tuning, and gives a faster convergence to the solution. In addition, the paper presents a computationally efficient symbolic formula for calculating the Hessian with respect to joint angles, which is essential for achieving realtime performance of the algorithm in high DOF configuration spaces. The method is validated successfully in simulation environment. Results for different methods (Newton, gradient descent and gradient descent with momentum) are compared in terms of quality of the path generated, oscillations, minimum distance to obstacles and convergence rate.
Wed, 01 Jan 2020 00:00:00 GMThttp://hdl.handle.net/10985/181962020-01-01T00:00:00ZSAFEEA, MohammadBEAREE, RichardNETO, PedroThis study investigates the application of Newton method to the problems of collision avoidance and path planning for robotic manipulators, especially robots with high Degrees of Freedom (DOF). The proposed algorithm applies to the potential fields method, where the Newton technique is used for performing the optimization. As compared to classical gradient descent method this implementation is mathematically elegant, enhances the performance of motion generation, eliminates oscillations, does not require gains tuning, and gives a faster convergence to the solution. In addition, the paper presents a computationally efficient symbolic formula for calculating the Hessian with respect to joint angles, which is essential for achieving realtime performance of the algorithm in high DOF configuration spaces. The method is validated successfully in simulation environment. Results for different methods (Newton, gradient descent and gradient descent with momentum) are compared in terms of quality of the path generated, oscillations, minimum distance to obstacles and convergence rate.On-line collision avoidance for collaborative robot manipulators by adjusting off-line generated paths: An industrial use case
http://hdl.handle.net/10985/17378
On-line collision avoidance for collaborative robot manipulators by adjusting off-line generated paths: An industrial use case
SAFEEA, Mohammad; NETO, Pedro; BEAREE, Richard
Human–robot collision avoidance is a key in collaborative robotics and in the framework of Industry 4.0. It plays an important role for achieving safety criteria while having humans and machines working side-by-side in unstructured and time-varying environment. This study introduces the subject of manipulator’s on-line collision avoidance into a real industrial application implementing typical sensors and a commonly used collaborative industrial manipulator, KUKA iiwa. In the proposed methodology, the human co-worker and the robot are represented by geometric primitives (capsules). The minimum distance and relative velocity between them is calculated, when human/obstacles are nearby the concept of hypothetical repulsion and attraction vectors is used. By coupling this concept with a mathematical representation of robot’s kinematics, a task level control with collision avoidance capability is achieved. Consequently, the off-line generated nominal path of the industrial task is modified on-the-fly so the robot is able to avoid collision with the co-worker safely while being able to fulfill the industrial operation. To guarantee motion continuity when switching between different tasks, the notion of repulsion-vector-reshaping is introduced. Tests on an assembly robotic cell in automotive industry show that the robot moves smoothly and avoids collisions successfully by adjusting the off-line generated nominal paths.
Tue, 01 Jan 2019 00:00:00 GMThttp://hdl.handle.net/10985/173782019-01-01T00:00:00ZSAFEEA, MohammadNETO, PedroBEAREE, RichardHuman–robot collision avoidance is a key in collaborative robotics and in the framework of Industry 4.0. It plays an important role for achieving safety criteria while having humans and machines working side-by-side in unstructured and time-varying environment. This study introduces the subject of manipulator’s on-line collision avoidance into a real industrial application implementing typical sensors and a commonly used collaborative industrial manipulator, KUKA iiwa. In the proposed methodology, the human co-worker and the robot are represented by geometric primitives (capsules). The minimum distance and relative velocity between them is calculated, when human/obstacles are nearby the concept of hypothetical repulsion and attraction vectors is used. By coupling this concept with a mathematical representation of robot’s kinematics, a task level control with collision avoidance capability is achieved. Consequently, the off-line generated nominal path of the industrial task is modified on-the-fly so the robot is able to avoid collision with the co-worker safely while being able to fulfill the industrial operation. To guarantee motion continuity when switching between different tasks, the notion of repulsion-vector-reshaping is introduced. Tests on an assembly robotic cell in automotive industry show that the robot moves smoothly and avoids collisions successfully by adjusting the off-line generated nominal paths.Modeling of an Ultrasonic Powder Transportation System
http://hdl.handle.net/10985/11434
Modeling of an Ultrasonic Powder Transportation System
CHITIC, Razvan; BEAREE, Richard; GIRAUD, Frédéric; LEMAIRE-SEMAIL, Betty; FAVRE, Monique; TIERCE, Pascal; JEHANNO, Jacky
This paper presents a new powder transportation system that uses a high frequency flexural stationary wave coupled with a low frequency horizontal displacement of a beam to produce the transport of the powder. The ultrasonic wave is produced with the help of piezoelectric cells glued under the beam and is used to decrease the friction coefficient between the powder and the beam surface.
Tue, 01 Jan 2013 00:00:00 GMThttp://hdl.handle.net/10985/114342013-01-01T00:00:00ZCHITIC, RazvanBEAREE, RichardGIRAUD, FrédéricLEMAIRE-SEMAIL, BettyFAVRE, MoniqueTIERCE, PascalJEHANNO, JackyThis paper presents a new powder transportation system that uses a high frequency flexural stationary wave coupled with a low frequency horizontal displacement of a beam to produce the transport of the powder. The ultrasonic wave is produced with the help of piezoelectric cells glued under the beam and is used to decrease the friction coefficient between the powder and the beam surface.