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Assembly process complexity in the production of manufactured products has received considerable attention in recent years. With the growing trend towards cyber-physical systems and the fourth industrial revolution, assembly research efforts must aim to develop efficient production systems incorporating robotic arms and flexible fixtures. The aim of the research was to investigate end effector and...
Kalman Filters are utilised for filtering and estimation in a large set of application. Here, this methodology is utilised for trajectory estimation of an underwater robot. In this work, three Kalman Filter methods are proposed for trajectory estimation. There are: Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF) and Central Difference Kalman Filter (CDKF). Simulation results are presented...
In a robotized ultrasound scanning system and more generally in any system which interacts with a human, the used control laws have to satisfy a safety of operating and functioning. Moreover these control laws have to guarantee a high precision in the medical gesture tracking, and especially within the framework of the ultrasound scanning, they assure the preservation of the ultrasound plane. The...
This paper discusses the learning of robot point-to-point motions via non-linear dynamical systems and Gaussian Mixture Regression (GMR). The novelty of the proposed approach consists in guaranteeing the stability of a learned dynamical system via Contraction theory. A contraction analysis is performed to derive sufficient conditions for the global stability of a dynamical system represented by GMR...
The paper presents a novel control method for the arm exoskeletons that takes into account the muscular force manipulability of the human arm. In contrast to classical controllers that provide assistance without considering the biomechanical properties of the human arm, we propose a control method that takes into account the configuration of the arm and the direction of the motion to effectively compensate...
Inference and decision making under uncertainty are essential in numerous robotics problems. In recent years, the similarities between inference and control triggered much work, from developing unified computational frameworks to pondering about the duality between the two. In spite of the aforementioned efforts, inference and control, as well as inference and belief space planning (BSP) are still...
In this paper we present a novel joint approach for optimising surface curvature and pose alignment. We present two implementations of this joint optimisation strategy, including a fast implementation that uses two frames and an offline multi-frame approach. We demonstrate an order of magnitude improvement in simulation over state of the art dense relative point-to-plane Iterative Closest Point (ICP)...
In this paper we present a novel geometric approach to motion planning for constrained robot systems. This problem is notoriously hard, as classical sampling-based methods do not easily apply when motion is constrained in a zero-measure submanifold of the configuration space. Based on results on the functional controllability theory of dynamical systems, we obtain a description of the complementary...
We present a graph-based algorithm for jointly estimating the positions of multiple ice-melting probes. The probes determine the distances relative to each other by measuring the signal propagation time of acoustic pulses. Furthermore, multiple other sensors, like an inertial measurement unit and a differential magnetometer system, are used to calculate the relative movement of the probes. The positions...
This paper presents a Cartesian adaptive control based on a robust Sliding Mode and Time Delay Estimation (CSMTDE) for controlling a redundant exoskeleton robot called ETS-MARSE subject to uncertain nonlinear dynamics and external forces. The robustness and accuracy are achieved by selecting a sliding Cartesian surface and a sliding joint surface. The combination between them is done by the nonlinear...
The paper compares application of Jacobian- and feedback-linearized models to control a nonlinear bicycle robot model. It includes simulation results of performance improvement in the case of weighting matrices and initial condition changes, including the analysis of energy-based indexes. In addition, the results also include comments concerning introduction of robustness to the control system.
This paper aims at providing a novel approach to modeling and controlling soft robots. Based on real-time Finite Element Method (FEM), we obtain a globally defined discrete-time kinematic model in the workspace of soft robots. From the kinematic equations, we deduce the soft-robot Jacobian matrix and discuss the conditions to avoid singular configurations. Then, we propose a novel observer based control...
In the application of physical human-robot interaction (pHRI), the collaboration between human and robot can significantly improve the production efficiency through combination of the human's flexible intelligence and the robot's consistent performance. In this application, however, it is an important concern to ensure the safety of the human and the robot. In the human guidance programming scenario,...
In this paper, the linearization of a nonlinear vector implicit differential equation that describes mechanical systems with application to robotics is established. In order to come to the results, a compact representation via Kronecker product of the partial derivative of the product of vector valued matrix functions is used. Two equivalent representations of the linearized model are derived. Once...
Whole-body control is crucial to fully exploit all the possible motions that redundant robots with a free-floating base can achieve. This paper presents a new open source and platform independent system that integrates whole-body operational-space control schemes based upon inverse kinematics for highly redundant robots. Contrary to other works, which heavily rely on complex underlying platforms and...
To enable automatic analysis of athletic movement, the first task is to recognize the athletic movements to be analyzed from a continuous motion data stream. Automated detection of athletic movement and the isolation of the recruited body parts would enable the analysis of sporting movements for improving sports performance and preventing possible injuries. In this paper, an unsupervised method for...
This paper presents a Hamilton-Jacobi theory based method to generate energy-optimal trajectories for the two-link planar manipulator which is a key component in the robot systems. We first build the mathematical model of the robot manipulator, then formulate a corresponding optimal control problem and solve it via the Hamilton-Jacobi theory. Compared with the existing methods, the presented framework...
The exoskeleton robotic rehabilitation training system is a branch of the field of robotics, it is the external mechanical system that is consistent with the similar joints of the human body, and attached to the human body. With the development of exoskeleton rehabilitation robotic system, the biomechanics influence of device should be considered in rehabilitation training. This paper proposes a novel...
During the last few decades, robotic grippers are developed by research community to solve grasping complexities of several objects as their primary objective. Due to the increasing demands of industries, many issues are rising and remain unsolved such as in-hand manipulation, placing object with appropriate posture. Operations like twisting, altering orientation of object, in a hand, requires significant...
In this work, we address the inverse kinematics problem for parallel mechanisms using a differential kinematics approach based on the recently proposed Filtered Inverse method. The key idea behind the method is to employ an inversion algorithm which dynamically estimates the inverse of the Jacobian matrix, rather than using the instantaneous calculation of the true inverse. An interesting property...
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