Object Manipulation by Multiple Arms of A Wheeled Mobile Robotic System

Multiple impedance control of space free-flying robots via virtual linkages

This paper presents an systematic dynamic modeling and performance analysis method of an over-constrained 2PUR-PSR parallel manipulator with parasitic motions, where P, U, S, and R represent the prismatic joint, universal joint, spherical joint, and revolute joint, respectively. The process of the deduction of the over-constrained forces/moment is given. The Newton–Euler approach and natural orthogonal complement method are adopted to establish two types of dynamic models with and without constrained forces/moments with the consideration of the over-constrained forces/moments. The dynamic manipulability ellipsoid, which measures the uniformity of changing the position and orientation of the manipulator’s moving platform, is adopted to evaluate the dynamic performance of the parallel manipulator. To show the feasibility of the proposed method, numerical simulations are conducted to investigate the dynamic models and performance of the 2PUR-PSR manipulator. The actuation forces, constrained forces/moments, and the compatible deformation are calculated. Distribution of the DME index is also obtained. The proposed modeling approach provides a fundamental basis for the structural optimization and control scheme design of the over-constrained parallel manipulator.

Dynamics and motion planning of a wheel-legged robot with two manipulator arms is discussed in this paper. This robot can move on flat surfaces fast, while it has the capability of moving over rough terrains. The two locomotion subsystems, i.e. wheeled mechanism and legged mechanism, will be discussed separately. Wheeled locomotion mechanism includes three wheels, two of them are in the back as active wheels with a differential driver. Legged locomotion mechanism includes two legs each with 4 revolute joints, i.e. 4 degrees of freedom (DOF). Two manipulators are installed on the main body to perform variant tasks, each of them is a PRR 3 DOF arm. Using direct path method (DPM) the robot kinematics is developed, and using Lagrangian approach the equations of motion are derived. A new method, called return path method (RPM), is proposed to add the constraints of the system to the kinetics equations without introducing additional variables. To eliminate the terms corresponding to the constraints, natural orthogonal complement method is used. Finally, motion planning of the robot is investigated to develop a stable gait planning procedure.

Dynamics modelling and Hybrid Suppression Control of space robots performing cooperative object manipulation

This work addresses a comparative analysis based on two finite element-based methodologies. The first methodology is constituted by a quasi-static procedure, established by Brazilian standard CONTRAN Resolution 755/2018. In this methodology, the FUP (Front Underrun Protection) device is discretized by finite element approach, and it is subjected to a concentrated force, applied at a specific point. The FUP device undergoes the inelastic process, and the equivalent plastic strain is evaluated. The second methodology is constituted by explicit dynamic contact modelling, a nonlinear analysis that considers the FUP device as a target body, while a vehicle as a moving body travels in different velocities. Beside, the numerical model adopted by second methodology is presented in detail, such as boundary condition and the finite element average dimension in the discretization. During the impact, the FUP device suffer a yielding process. The plastic strain, contact force and impact energy are assessed for both methodologies. The equivalent plastic strain indicate that the collision with vehicle colliding with the device with a velocity lower or equals to 30 km/h presents a similar result obtained by quasi-static procedure. However, for collision involving vehicle velocity higher than 40 km/h, the explicit dynamic contact simulation provides more reasonable results. Furthermore, the impact energy and force obtained by both methodologies indicate that the quasi-static procedure provides a value lower than those obtained by explicit dynamic contact modelling, indicating the assertiveness and applicability of contact modelling.

A power-type varying gain discrete-time recurrent neural network for solving time-varying linear system

Current systems for object detection in video sequences rely on explicit dynamical models like Kalman filters or hidden Markov models. There is significant overhead needed in the development of such systems as well as the a priori assumption that the object dynamics can be described with such a dynamical model. This paper describes a new pattern classification technique for object detection in video sequences that uses a rich, overcomplete dictionary of wavelet features to describe an object class. Unlike previous work where a small subset of features was selected from the dictionary, this system does no feature selection and learns the model in the full 1,326 dimensional feature space. Comparisons using different sized sets of several types of features are given. We extend this representation into the time domain without assuming any explicit model of dynamics. This data driven approach produces a model of the physical structure and short-time dynamical characteristics of people from a training set of examples; no assumptions are made about the motion of people, just that short sequences characterize their dynamics sufficiently for the purposes of detection. One of the main benefits of this approach is that transient false positives are reduced. This technique compares favorably with the static detection approach and could be applied to other object classes. We also present a real-time version of one of our static people detection systems.

We developed a hierarchical framework for the representation of variable compound objects in 2-dimensional images in terms of an adaptive two-level shape model that can be used for recognition and classification tasks. A control instance guides the local search for shapes by managing knowledge about variable spatial relations between single deformable shapes that is uniformly represented through explicit dynamic models. Temporary and permanent memory of past successful searches are used to accomplish a purposeful search, and to improve the a-priori model using generated training data. The framework is applied to the labeling of Heschl's gyrus in flattened parametric representations of the human cortex (flat maps), which is of great interest with respect to multi-subject fMRI studies. Results indicate the models' potential for recognition and classification without the need for prior training.

This paper presents a comparison of three models which can be used to identify the minimum dynamic parameters of robots: a dynamic model which depends on the joint acceleration and needs an explicit derivation of the velocity, called the explicit dynamic model; a dynamic model which avoids using explicit acceleration but needs the derivation of a function of the velocity, called the implicit dynamic model; and the energy model, which doesn't need neither acceleration nor implicit velocity derivation. A power model, which is the differential expression of the energy model, is introduced to enlighten the comparison between dynamic and energy models and to improve the filtering of the energy model. Theoretical analysis is carried out from a filtering point of view and clearly shows the differences between the 3 identification models. These results are checked from comparing simulated and experimental identifications of the dynamic parameters of a planar SCARA prototype robot.

Parameterizing the formation rate of new particles: The effect of nuclei self-coagulation

This paper describes the derivation of an explicit and general dynamics model for nonredundant parallel manipulators according to a novel formalism and Jacobian/Hessian matrices of the constraint equations. This dynamic model is based solely on tensor theory and can be used for both inverse and direct dynamics. In the present model, all dynamic effects are directly derived from the system's structural parameters and generalized variables, without any intermediate complex computations such as velocity and acceleration-based energy, differentiation, or acceleration calculations, and without the need for symbolic expressions; consequently, they can be computed completely online. Next, an example of parallel manipulator is used in this study to verify the proposed general formulation in terms of simplicity, correctness, and efficiency. The model is more efficient in providing explicit equations of motion and can even compete with implicit formulations for a specific manipulator structure. In addition, it can be further optimized to perform real-time control. Finally, to address uncertainties in the system, robust model-based control is implemented based on the proposed model. Hence, this paper provides a theoretical basis for control strategies and structural parameter optimization.

Effective connectivity within the neural system for object-directed action representation during aware and unaware tool processing

Robotics is a scientific discipline which includes the operation and development of robots and other fields of computer science, as well as electrical and mechanical engineering and high-performance modular control systems. This paper reports the first results of a research project that uses a previously developed MES - Modular Electronic System for autonomous mobile robots and for developing robots to use the MES in other scientific applications. This approach offers the ability to build a scalable and flexible control system with only a few modules. A novel feature of our approach is its modular integration of electronics with the ability to multitask, which can be adapted for particular applications. We demonstrate the robustness of this approach in controlling an indoor mobile robot for the EUROBOT 2009 and 2010.

Wheeled mobile robot (WMR) is usually applicable for executing an operational task around complicated environment; skidding and slipping phenomena unavoidably appear during the motion, which thus can compromise the accomplishment of the task. This paper investigates the trajectory tracking control problem of WMRs via disturbance rejection in the presence of wheel skidding and slipping phenomena. The kinematic and dynamic models with the perturbed nonholonomic constraints are established. The trajectory tracking control scheme at the dynamic level is designed so that the mobile robot system can track the virtual velocity asymptotically, and counteract the perturbation caused by the unknown skidding and slipping of wheels. Both simulation and experimental works are conducted, and the results prove the performance of the proposed control scheme is effective in terms of tracking precision and disturbance attenuation.

This paper analyzes the control of a mobile robotic system that utilizes a serpentine robotic tail to assist in the maneuvering and stabilization of quadrupedal locomotion. The goal of this research is to reduce the design and control complexity required in the robot's legs by providing a separate mechanism to help the mobile robot steer and recover from disturbances. The design and dynamic models for a quadrupedal robotic platform's yaw, pitch and roll are presented, along with the design and dynamic model of the roll-revolute-revolute robotic tail (R3-RT). Dynamic tail configuration controllers are designed to enable different system functionalities, including yaw-angle turning and pitch/roll-angle stabilization. Case studies are simulated in MATLAB to demonstrate the proposed functionalities.