Control of robotic motion with neuron-like elements

2002 ◽  
Author(s):  
S. Wolpert
Keyword(s):  
Robotic Motion

scholarly journals Specifying and optimizing robotic motion for visual quality inspection

2021 ◽  
Vol 72 ◽  
pp. 102200
Author(s):  
Zvezdan Lončarević ◽  
Andrej Gams ◽  
Simon Reberšek ◽  
Bojan Nemec ◽  
Jure Škrabar ◽  
...  
Keyword(s):  
Visual Quality ◽  
Quality Inspection ◽  
Robotic Motion

Robotic motion compensation for bone movement, using ultrasound images

2015 ◽  
Vol 42 (5) ◽  
pp. 466-474 ◽  
Author(s):  
P.M.B. Torres ◽  
P. J. S. Gonçalves ◽  
J.M.M. Martins
Keyword(s):  
Motion Compensation ◽  
Optical Measurement ◽  
Three Dimensional ◽  
Point Clouds ◽  
Robotic System ◽  
Ultrasound Images ◽  
Bone Drilling ◽  
Content Type ◽  
3D Point Clouds ◽  
Robotic Motion

Purpose – The purpose of this paper is to present a robotic motion compensation system, using ultrasound images, to assist orthopedic surgery. The robotic system can compensate for femur movements during bone drilling procedures. Although it may have other applications, the system was thought to be used in hip resurfacing (HR) prosthesis surgery to implant the initial guide tool. The system requires no fiducial markers implanted in the patient, by using only non-invasive ultrasound images. Design/methodology/approach – The femur location in the operating room is obtained by processing ultrasound (USA) and computer tomography (CT) images, obtained, respectively, in the intra-operative and pre-operative scenarios. During surgery, the bone position and orientation is obtained by registration of USA and CT three-dimensional (3D) point clouds, using an optical measurement system and also passive markers attached to the USA probe and to the drill. The system description, image processing, calibration procedures and results with simulated and real experiments are presented and described to illustrate the system in operation. Findings – The robotic system can compensate for femur movements, during bone drilling procedures. In most experiments, the update was always validated, with errors of 2 mm/4°. Originality/value – The navigation system is based entirely on the information extracted from images obtained from CT pre-operatively and USA intra-operatively. Contrary to current surgical systems, it does not use any type of implant in the bone to track the femur movements.

Robotic Motion Coordination Based on a Geometric Deformation Measure

2021 ◽  
pp. 1-11
Author(s):  
Miguel Aranda ◽  
Jose Sanchez ◽  
Juan Antonio Corrales Ramon ◽  
Youcef Mezouar
Keyword(s):  
Motion Coordination ◽  
Robotic Motion ◽  
Geometric Deformation

Style-Based Robotic Motion in Contemporary Dance Performance

2014 ◽  
pp. 205-229 ◽  
Author(s):  
Amy LaViers ◽  
Lori Teague ◽  
Magnus Egerstedt
Keyword(s):  
Contemporary Dance ◽  
Dance Performance ◽  
Robotic Motion

Energy-Optimal Motion Trajectory of an Omni-Directional Mecanum-Wheeled Robot via Polynomial Functions

Robotica ◽  
2019 ◽  
Vol 38 (8) ◽  
pp. 1400-1414
Author(s):  
Li Xie ◽  
Karl Stol ◽  
Weiliang Xu
Keyword(s):  
Energy Consumption ◽  
Polynomial Functions ◽  
Heavy Duty ◽  
Optimal Motion ◽  
Wheeled Robots ◽  
Motion Trajectories ◽  
Decision Variables ◽  
Robotic Motion ◽  
Wheeled Robot ◽  
Mecanum Wheel

SUMMARYThe Mecanum wheel is one of the practical omni-directional wheel designs in industry, especially for heavy-duty tasks in a confined floor. An issue with Mecanum-wheeled robots is inefficient use of energy. In this study, the robotic motion trajectories are optimized to minimize the energy consumption, where a robotic path is expressed in polynomial functions passing through a given set of via points, and a genetic algorithm is used to find the polynomial’s coefficients being decision variables. To attempt a further reduction in the energy consumption, the via points are also taken as decision variables for the optimization. Both simulations and experiments are conducted, and the results show that the optimized trajectories result in a significant reduction in energy consumption, which can be further lowered when the via points become decision variables. It is also found that the higher the order of the polynomials the larger the reduction in the energy consumption.

scholarly journals Design and Feasibility Study of a Leg-exoskeleton Assistive Wheelchair Robot with Tests on Gluteus Medius Muscles

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 548 ◽  
Author(s):  
Gao Huang ◽  
Marco Ceccarelli ◽  
Qiang Huang ◽  
Weimin Zhang ◽  
Zhangguo Yu ◽  
...  
Keyword(s):  
Lower Limb ◽  
Gluteus Medius ◽  
Lower Limbs ◽  
Gluteus Medius Muscle ◽  
Emg Signal ◽  
Assistive Robot ◽  
Robotic Motion ◽  
Leg Motion ◽  
Motion Characteristics ◽  
Exercise Efficiency

The muscles of the lower limbs directly influence leg motion, therefore, lower limb muscle exercise is important for persons living with lower limb disabilities. This paper presents a medical assistive robot with leg exoskeletons for locomotion and leg muscle exercises. It also presents a novel pedal-cycling actuation method with a crank-rocker mechanism. The mechanism is driven by a single motor with a mechanical structure that ensures user safety. A control system is designed based on a master-slave control with sensor fusion method. Here, the intended motion of the user is detected by pedal-based force sensors and is then used in combination with joystick movements as control signals for leg-exoskeleton and wheelchair motions. Experimental data is presented and then analyzed to determine robotic motion characteristics as well as the assistance efficiency with attached electromyogram (EMG) sensors. A typical muscle EMG signal analysis shows that the exercise efficiency for EMG activated amplitudes of the gluteus medius muscles approximates a walking at speed of 3 m/s when cycling at different speeds (i.e., from 16 to 80 r/min) in a wheelchair. As such, the present wheelchair robot is a good candidate for enabling effective gluteus medius muscle exercises for persons living with gluteus medius muscle disabilities.

scholarly journals Grasp Posture Control of Wearable Extra Robotic Fingers with Flex Sensors Based on Neural Network

Electronics ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 905 ◽  
Author(s):  
Joga Dharma Setiawan ◽  
Mochammad Ariyanto ◽  
M. Munadi ◽  
Muhammad Mutoha ◽  
Adam Glowacz ◽  
...  
Keyword(s):  
Neural Network ◽  
Haptic Feedback ◽  
Control Method ◽  
Middle Finger ◽  
Object Manipulation ◽  
Robotic System ◽  
Robotic Motion ◽  
Trained Neural Network ◽  
Flex Sensors ◽  
Robotic Fingers

This study proposes a data-driven control method of extra robotic fingers to assist a user in bimanual object manipulation that requires two hands. The robotic system comprises two main parts, i.e., robotic thumb (RT) and robotic fingers (RF). The RT is attached next to the user’s thumb, while the RF is located next to the user’s little finger. The grasp postures of the RT and RF are driven by bending angle inputs of flex sensors, attached to the thumb and other fingers of the user. A modified glove sensor is developed by attaching three flex sensors to the thumb, index, and middle fingers of a wearer. Various hand gestures are then mapped using a neural network. The input data of the robotic system are the bending angles of thumb and index, read by flex sensors, and the outputs are commanded servo angles for the RF and RT. The third flex sensor is attached to the middle finger to hold the extra robotic finger’s posture. Two force-sensitive resistors (FSRs) are attached to the RF and RT for the haptic feedback when the robot is worn to take and grasp a fragile object, such as an egg. The trained neural network is embedded into the wearable extra robotic fingers to control the robotic motion and assist the human fingers in bimanual object manipulation tasks. The developed extra fingers are tested for their capacity to assist the human fingers and perform 10 different bimanual tasks, such as holding a large object, lifting and operate an eight-inch tablet, and lifting a bottle, and opening a bottle cap at the same time.

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