Deeply-learnt damped least-squares (DL-DLS) method for inverse kinematics of snake-like robots

Omisore, Olatunji Mumini; Han, Sunyoung; Ren, Li; Elazab, Ahmed; Li, Hui; Abdelhamid, Talaat; Azeez, Nureni Ayofe; Wang, Lei

doi:10.1016/j.neunet.2018.06.018

Cited by 21 publications

(19 citation statements)

References 30 publications

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“…Other works focused more on the damping factor, which also impacts on accuracy and computation time of the DLS algorithm. In particular, addressing snake-like robots employed in micro-surgery applications, where hard accuracy and time requirements are present, Omisore et al [10] adopted a deep-learning approach to optimally adjust the damping factor for every target point of the DLS, obtaining speed-up and accuracy improvements. Damping factor optimization is also desired for enhancing behavior of the DLS algorithm when passing close to singularities.…”

Section: B Damped Least Square For Inverse Kinematicsmentioning

confidence: 99%

“…Associated [26] no none 4/6 no N/A [32] no none 4 no SW [33] numerical error 7 no SW [34], [35] machine learning step 6/7 no SW [10] machine learning lambda 8 no SW [36] genetic lambda 6 no N/A [37] analytical lambda 6 no SW THIS WORK no step,lambda 4 yes HW we analyze two different MATLAB implementations that we made available as an open-data [12] of the CERBERO project. We will refer to these implementation as:…”

Section: Workmentioning

confidence: 99%

“…Performance and accuracy are key requirements in robotic applications, not only in the space exploration field. For instance, also surgery [10] and industrial [11] application fields require an accurate trajectory control during their tasks execution, even in the proximity of singularity points. At the same time, if online trajectory calculation is enabled, the time requested to evaluate it may be critical in achieving responsiveness.…”

Section: Introductionmentioning

confidence: 99%

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Feasibility Study and Porting of the Damped Least Square Algorithm on FPGA

Fanni

Rubattu

et al. 2020

IEEE Access

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Modern embedded computing platforms used within Cyber-Physical Systems (CPS) are nowadays leveraging more and more often on heterogeneous computing substrates, such as newest Field Programmable Gate Array (FPGA) devices. Compared to general purpose platforms, which have a fixed datapath, FPGAs provide designers the possibility of customizing part of the computing infrastructure, to better shape the execution on the application needs/features, and offer high efficiency in terms of timing and power performance, while naturally featuring parallelism. In the context of FPGA-based CPSs, this paper has a two fold mission. On the one hand, it presents an analysis of the Damped Least Square (DLS) algorithm for a perspective hardware implementation. On the other hand, it describes the implementation of a robotic arm controller based on the DLS to numerically solve Inverse Kinematics problems over a heterogeneous FPGA. Assessments involve a Trossen Robotics WidowX robotic arm controlled by a Digilent ZedBoard provided with a Xilinx Zynq FPGA that computes the Inverse Kinematic.

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Section: B Damped Least Square For Inverse Kinematicsmentioning

confidence: 99%

Section: Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Feasibility Study and Porting of the Damped Least Square Algorithm on FPGA

Fanni

Rubattu

et al. 2020

IEEE Access

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“…While robotic mechanisms with soft actuation and deformable joints are generally 2 of 22 used in the context of flexible robotics, rigid serial-link robots have also been proposed and adapted to enhance MIS procedures that involve intrabody and intraluminal navigations [2]. While the robots are capable of flexible intrabody movements in certain human cavities, links in the prototypes that have redundant parts can be utilized for effective obstacle and singularity avoidance by using operative kinodynamics model [3,4]. Some existing surgical robotic systems, such as Zeus and da Vinci robotic platforms, adopt parallel-link design mechanisms for flexible access during surgical interventions.…”

Section: Introductionmentioning

confidence: 99%

Motion and Trajectory Constraints Control Modeling for Flexible Surgical Robotic Systems

et al. 2020

Self Cite

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Success of the da Vinci surgical robot in the last decade has motivated the development of flexible access robots to assist clinical experts during single-port interventions of core intrabody organs. Prototypes of flexible robots have been proposed to enhance surgical tasks, such as suturing, tumor resection, and radiosurgery in human abdominal areas; nonetheless, precise constraint control models are still needed for flexible pathway navigation. In this paper, the design of a flexible snake-like robot is presented, along with the constraints model that was proposed for kinematics and dynamics control, motion trajectory planning, and obstacle avoidance during motion. Simulation of the robot and implementation of the proposed control models were done in Matlab. Several points on different circular paths were used for evaluation, and the results obtained show the model had a mean kinematic error of 0.37 ± 0.36 mm with very fast kinematics and dynamics resolution times. Furthermore, the robot's movement was geometrically and parametrically continuous for three different trajectory cases on a circular pathway. In addition, procedures for dynamic constraint and obstacle collision detection were also proposed and validated. In the latter, a collision-avoidance scheme was kept optimal by keeping a safe distance between the robot's links and obstacles in the workspace. Analyses of the results showed the control system was optimal in determining the necessary joint angles to reach a given target point, and motion profiles with a smooth trajectory was guaranteed, while collision with obstacles were detected a priori and avoided in close to real-time. Furthermore, the complexity and computational effort of the algorithmic models were negligibly small. Thus, the model can be used to enhance the real-time control of flexible robotic systems.

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“…Based on the Gaussian distribution of the damping factor, the Gaussian function is applied to determine the damping factor, which can continuously transition from undamped to damped, making the motion more stable and reducing errors. A deeply learnt damped least-squares method is proposed for solving IK of the spatial snake-like robot in [10]. A deep network is built for prediction of the unique damping factor required for each target point.…”

Section: Introductionmentioning

confidence: 99%

Two Optimized General Methods for Inverse Kinematics of 6R Robots Based on Machine Learning

Wang

Cao

Chen

et al. 2020

Mathematical Problems in Engineering

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For the 6R robot, there is no analytical solution for some configurations, so it is necessary to analyse inverse kinematics (IK) by the general solution method, which cannot achieve high precision and high speed as the analytical solution. With the expansion of application fields and the complexity of application scenarios, some robots with special configuration have become the research hotspot, and more high-speed and high-precision general algorithms are still being explored and studied. The present paper optimized two general solutions. Elimination is a numerical solution, which has high accuracy, but the solution process is complex and time-consuming. The present paper optimized the elimination method, derived the final matrix expression directly through complex coefficient extraction and simplifying operation, and realized one-step solution. The solving speed was reduced to 15% of the original, and the integrity of the method was supplemented. This paper proposed a new optimization method for the Gaussian damped least-squares method, in which the variable step-size coefficient is introduced and the machine learning method is used for the research. It was proved that, on the basis of guaranteeing the stability of motion, the average number of iterations can be effectively reduced and was only 4-5 times, effectively improving the solving speed.

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Deeply-learnt damped least-squares (DL-DLS) method for inverse kinematics of snake-like robots

Cited by 21 publications

References 30 publications

Feasibility Study and Porting of the Damped Least Square Algorithm on FPGA

Feasibility Study and Porting of the Damped Least Square Algorithm on FPGA

Motion and Trajectory Constraints Control Modeling for Flexible Surgical Robotic Systems

Two Optimized General Methods for Inverse Kinematics of 6R Robots Based on Machine Learning

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