Task Space Torque Profile Adaptations for Dynamical Human-Robot Motion Transfer

2018 ◽  
pp. 44-52 ◽  
Author(s):  
Tadej Petrič ◽  
Andrej Gams
Keyword(s):  
Robot Motion ◽  
Task Space

scholarly journals Pengendalian konvergensi eksponensial untuk omnidirectional mobile robot dengan empat roda

JURNAL ELTEK ◽  
2020 ◽  
Vol 18 (1) ◽  
pp. 108
Author(s):  
Muhammad Jodi Pamenang ◽  
Indrazno Siradjuddin ◽  
Budhy Setiawan
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Motion Control ◽  
Kinematic Model ◽  
Robot Motion ◽  
Control Law ◽  
Task Space ◽  
Wheeled Mobile Robots ◽  
Simulation Experiments ◽  
Omnidirectional Mobile Robot

Tujuan mendasar dari kontrol gerak mobile robot adalah untuk mengarahkan robot ke posisi yang diberikan secara acak pada ruang 2D. Mobile robot dengan roda omni memiliki sifat holonomic di mana memiliki keunggulan kelincahan dan permasalahan pengendalian gerak hanya pada sisi aktuator, sedangkan mobile robot dengan roda konvensional, memiliki permasalahan tambahan pengendalian gerak dalam ruang area operasional robot. Karenanya, robot omni lebih gesit untuk bergerak dalam konfigurasi ruang area kerja apa pun. Makalah ini menyajikan model kontrol konvergensi eksponensial berbasis model untuk mobile robot omnidirectional roda empat. Kontrol yang diusulkan menjamin penurunan kesalahan secara eksponensial dari gerakan robot ke setiap posisi robot yang diinginkan. Pembahasan meliputi model kinematik dan kontrol dari robot bergerak omnidirectional roda empat dan eksperimen simulasi yang telah dilakukan untuk memverifikasi kinerja kontrol yang meliputi lintasan robot 2D, serta nilai error atau kesalahan pada kontrol robot. Hasil dari eksperimen simulasi menunjukkan keefektifan kontrol yang diusulkan. Mobile robot telah bergerak ke posisi yang diinginkan pada garis lurus dengan tujuan robot yang akurat dan niali error atau kesalahan yang didapat ialah |0.02735| serta grafik error telah menurun secara eksponensial.   The fundamental objective of a mobile robot motion control is to navigate the robot to any given arbitrary posture in which robot 2D location and its heading are concerned. Mobile robots with omni wheels have a holonomic properties the advantage is of agility and motion control problems only on the actuator, while mobile robots with conventional wheels, have a problem of motion control the robot in task space. Therefore, the omni-wheeled mobile robots are more agile to move in any task space configuration.  This paper presents a model based exponential convergence control law for a four-wheeled omnidirectional mobile robot. The proposed control law guarantees an exponential error decay of mobile robot motion to any given desired robot posture. The kinematic model and the control law of a four-wheeled omnidirectional mobile robot are discussed. Simulation experiments have been conducted to verify the control law performances which include the 2D robot trajectory, the error signals, and the robot control signals. Results from simulation experiments show the effectiveness of the proposed control law. Mobile robot has moved to the desired position in a straight line with the aim of the robot that is accurate and the error or error obtained is | 0.02735 | and the error graph has decreased exponentially

Deriving Humanlike Arm Hand System Poses

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Minas Liarokapis ◽  
Charalampos P. Bechlioulis ◽  
Panagiotis K. Artemiadis ◽  
Kostas J. Kyriakopoulos
Keyword(s):  
Inverse Kinematics ◽  
Forward Kinematics ◽  
Robot Motion ◽  
Robot Arm ◽  
Task Space ◽  
Optimization Scheme ◽  
Human Arm ◽  
Robot Hands ◽  
Minimal Design ◽  
Mapping Scheme

Robots are rapidly becoming part of our lives, coexisting, interacting, and collaborating with humans in dynamic and unstructured environments. Mapping of human to robot motion has become increasingly important, as human demonstrations are employed in order to “teach” robots how to execute tasks both efficiently and anthropomorphically. Previous mapping approaches utilized complex analytical or numerical methods for the computation of the robot inverse kinematics (IK), without considering the humanlikeness of robot motion. The scope of this work is to synthesize humanlike robot trajectories for robot arm-hand systems with arbitrary kinematics, formulating a constrained optimization scheme with minimal design complexity and specifications (only the robot forward kinematics (FK) are used). In so doing, we capture the actual human arm-hand kinematics, and we employ specific metrics of anthropomorphism, deriving humanlike poses and trajectories for various arm-hand systems (e.g., even for redundant or hyper-redundant robot arms and multifingered robot hands). The proposed mapping scheme exhibits the following characteristics: (1) it achieves an efficient execution of specific human-imposed goals in task-space, and (2) it optimizes anthropomorphism of robot poses, minimizing the structural dissimilarity/distance between the human and the robot arm-hand systems.

Hierarchical switching in a multi-dimensional task space is not induced by specific task cues

2001 ◽  
Vol 209 (2) ◽  
pp. 105-117 ◽  
Author(s):  
Thomas Kleinsorge ◽  
Herbert Heuer ◽  
Volker Schmidtke
Keyword(s):  
Specific Task ◽  
Task Space ◽  
Basic Pattern ◽  
Task Representation ◽  
Switching Mechanism ◽  
Factorial Combination ◽  
Individual Task ◽  
The Individual ◽  
The Way

Summary. When participants have to shift between four tasks that result from a factorial combination of the task dimensions judgment (numerical vs. spatial) and mapping (compatible vs. incompatible), a characteristic profile of shift costs can be observed that is suggestive of a hierarchical switching mechanism that operates upon a dimensionally ordered task representation, with judgment on the top and the response on the bottom of the task hierarchy ( Kleinsorge & Heuer, 1999 ). This switching mechanism results in unintentional shifts on lower levels of the task hierarchy whenever a shift on a higher level has to be performed, leading to non-shift costs on the lower levels. We investigated whether this profile depends on the way in which the individual task dimensions are cued. When the cues for the task dimensions were exchanged, the basic pattern of shift costs was replicated with only minor modifications. This indicates that the postulated hierarchical switching mechanism operates independently of the specifics of task cueing.

Upper-limb Rehabilitation Robot Motion Control Based on Dynamic Interpolation

ROBOT ◽  
2012 ◽  
Vol 34 (5) ◽  
pp. 539 ◽  
Author(s):  
Lizheng PAN ◽  
Aiguo SONG ◽  
Guozheng XU ◽  
Huijun LI ◽  
Baoguo XU
Keyword(s):  
Motion Control ◽  
Upper Limb ◽  
Robot Motion ◽  
Rehabilitation Robot ◽  
Upper Limb Rehabilitation ◽  
Limb Rehabilitation

Mechanical assessment of time optimal robot motion

2004 ◽  
Vol 33 (2) ◽  
pp. 121-128 ◽  
Author(s):  
R. W. Longman ◽  
H. G. Bock ◽  
G. Giese
Keyword(s):  
Robot Motion ◽  
Time Optimal

scholarly journals Task-space regulation of rigid-link electrically-driven robots with uncertain kinematics using neural networks

2021 ◽  
Vol 54 (1-2) ◽  
pp. 102-115
Author(s):  
Wenhui Si ◽  
Lingyan Zhao ◽  
Jianping Wei ◽  
Zhiguang Guan
Keyword(s):  
Neural Networks ◽  
Asymptotic Stability ◽  
Control Method ◽  
Joint Space ◽  
Robot Kinematics ◽  
Rbf Neural Networks ◽  
Task Space ◽  
Actuator Dynamics ◽  
Rigid Link ◽  
On Line

Extensive research efforts have been made to address the motion control of rigid-link electrically-driven (RLED) robots in literature. However, most existing results were designed in joint space and need to be converted to task space as more and more control tasks are defined in their operational space. In this work, the direct task-space regulation of RLED robots with uncertain kinematics is studied by using neural networks (NN) technique. Radial basis function (RBF) neural networks are used to estimate complicated and calibration heavy robot kinematics and dynamics. The NN weights are updated on-line through two adaptation laws without the necessity of off-line training. Compared with most existing NN-based robot control results, the novelty of the proposed method lies in that asymptotic stability of the overall system can be achieved instead of just uniformly ultimately bounded (UUB) stability. Moreover, the proposed control method can tolerate not only the actuator dynamics uncertainty but also the uncertainty in robot kinematics by adopting an adaptive Jacobian matrix. The asymptotic stability of the overall system is proven rigorously through Lyapunov analysis. Numerical studies have been carried out to verify efficiency of the proposed method.

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