First Report of Botryosphaeria dothidea Causing Stem Blight of Dioscorea oppositifolia in China.

Dioscorea oppositifolia Thunb. (Chinese yam) is one of the traditional foods and medicinal plants in China. It has nutritional and medicinal value and plays an important role in treatment of diabetes and hypertension. In 2018, stem blight was first observed on the stalks of D. oppositifolia in fields of Anguo City (115°27' N; 38°46' E), Hebei Province, China. Over 400 plants were surveyed in four fields, and nearly 30% of the plants were infected. At the initial stage of the disease, there were dark brown spots on the stems and in later stages the leaves and stems withered. To identify the pathogen, 10 symptomatic stalks were collected, and one diseased area was taken out from each sample. Small square stalk pieces (3 to 5 mm) were obtained with sterile scissors from the junction of infected and healthy tissues, sterilized with sodium hypochlorite (10%) for 1 min, followed by washing in sterile water three times, then pieces were transferred to potato dextrose agar (PDA) plates for 7 days at 25°C. The fungal isolates were purified by single-spore isolation. A total of three species of fungi were isolated, and initial pathogenicity tests found that one fungal species could cause the disease symptoms on D. oppositifolia stems. This pathogen was grown on PDA plates in the dark at 25 °C for 10 days. In the beginning, the colonies were white, and as the culture time was extended, the color of the colonies became darker and then became black. Conidia forming on pycnidia were one-celled, hyaline, aseptate, and ovoid, with dimensions of 4.6 to 7.6 × 2.6 to 4.8 µm (n=100). Mycelial DNA was extracted from a 7-day-old culture, and PCR amplifications were performed using primers ITS1/ITS4 and ß-tubF/ß-tubR (Glass and Donaldson 1995; White et al. 1990). BLAST searches at GenBank showed 100.00% nucleotide sequence identity for the ITS sequence with Botryosphaeria dothidea strain sdxf6 (MG282093; 545/545 bp) and for ß-tubulin 99.76% identity with B. dothidea strain SD-B8 (KP183131; 411/412 bp). Sequences from these regions were deposited in GenBank (ITS: OP104323; ß-tubulin: OK669147). Morphological and molecular results confirmed this species as B. dothidea (Angelica et al. 2017; Bernard et al. 2004). To inoculate plants, pathogen was grown on PDA at 25°C in the dark for 15 days, after which a spore suspension (3×105 spores/mL) was prepared by flooding the agar surface with sterilized double-distilled water. Pathogenicity tests were conducted by stem inoculation of 6-month-old healthy D. oppositifolia plants. The stems were wounded by lightly rubbing with a steel sponge, and the wounded stem was wrapped in sterile cotton treated with 1 mL of the spore suspension, then the plants were covered with plastic to maintain a moist environment for 72 h. Control plants were inoculated with sterile water. Inoculated and control plants (ten each) were kept in a moist chamber (25°C, 16-h light and 8-h dark period, 75% relative humidity). After 15 days, all of the inoculated plants showed dark brown spots on the stems, and the symptoms were the same as those in the field, while the controls were healthy. After 30 days, all of the inoculated but none of the control D. oppositifolia plants showed leaf wilting or leaf withering. Isolates from the inoculated and infected leaves were identified as B. dothidea by DNA sequencing with primers ITS1/ITS4 and ß-tubF/ß-tubR, fulfilling Koch's postulates. To our knowledge, this is the first report of B. dothidea causing stem blight on D. oppositifolia. The disease poses a threat to the production of D. oppositifolia, and management strategies need to be developed.

Transcriptome analysis in the thiamethoxam resistance of seven-spot ladybird beetle, Coccinella septempunctata (Coleoptera: Coccinellidae).

The seven-spot ladybird beetle, Coccinella septempunctata Linnaeus (Coleoptera: Coccinellidae) has been used as the main biological control agent against all kinds of aphids in farmland and greenhouse. In this study, a thiamethoxam-resistant strain (ThR) and a susceptible strain (SS) of seven-spot ladybird beetle were established, and differentially expressed genes (DEGs) associated with thiamethoxam resistance were recorded through de novo Illumina HiSeq 4000 sequencing. A total of 53.5 Gb of clean data were obtained and finally assembled into 21,217 unigenes from ThR and SS transcriptomes. 1798 DEGs were identified between the ThR libraries and the SS libraries, including 560 up-regulated genes and 1238 down-regulated genes. Some cytochrome p450 monooxygenases (CYP450s), UDP-glycosyltransferases (UGTs), esterases (ESTs) and ATP-binding cassette (ABC) transporters were observed to be up-regulated and the nicotinic acetylcholine receptors (nAChRs) α subunit gene down-regulated in the ThR strain compared to the SS strain. This study provides genetic information for further studies on thiamethoxam resistance mechanisms in the seven-spot ladybird beetle.

Sublethal and transgenerational effects of exposures to the thiamethoxam on the seven-spotted lady beetle, Coccinella septempunctata L. (Coleoptera: Coccinellidae).

The seven-spot ladybird beetle, Coccinella septempunctata L. (Coleoptera: Coccinellidae) has been used as the major natural enemy insect against many kinds of aphids in environment. Thiamethoxam is a second-generation neonicotinoid insecticide and commonly used to control various aphids, but it also has adverse effects on natural enemies. Therefore, the sublethal effects of thiamethoxam on the offspring of C. septempunctata were studied. For the adults of C. septempunctata, the LD30 of F0, F5, F10 and F15 generations were 0.039, 0.136, 0.243, 0.417 µg adult-1, respectively. The LD50 of F0, F5, F10 and F15 generations were 0.072, 0.275, 0.435, 0.819 µg adult-1, respectively. The resistance ratio of the F15 generation was 11.4-fold higher than that of the F0 generation. The preadult duration ( F0 = 17.4 d, F5 = 20.0 d, F10 = 19.1 d, F15 = 18.0 d) and adult preoviposition period ( F0 = 7.39 d, F5 = 8.07 d, F10 = 9.32 d, F15 = 8.03 d) of C. septempunctata were prolonged, and the fecundity ( F0 = 1690.10, F5 =1686.93, F10 = 1119.40, F15 = 752.87), oviposition period ( F0 = 42.84 d, F5 =40.33 d, F10 = 40.72 d, F15 = 30.84 d) and total longevity ( F0 = 86.7 d, F5 =81.3 d, F10 = 82.0 d, F15 = 74.0 d) were reduced by long-term exposure to sublethal dosage (LD30) of thiamethoxam. Population parameters (r, λ, R0, and T) were significantly reduced in F5, F10 and F15 generation. In addition, the predation function of F15 generation was reduced by sublethal dosage exposure of thiamethoxam. These results showed the negative impacts of sublethal thiamethoxam on the offspring of predators.

Molecular Characterization of Vitellogenin and Its Receptor in Spodoptera frugiperda (J. E. Smith, 1797), and Their Function in Reproduction of Female.

The fall armyworm Spodoptera frugiperda is a highly polyphagous invasive pest. The strong reproductive capacity is an important factor in the rapid colonization and expansion of S. frugiperda. Vitellogenin (Vg) and vitellogenin receptor (VgR) play important roles in insect reproduction. As the precursor of vitellin (Vn), Vg provides essential nutrition for embryonic development, and VgR mediates the uptake of Vg by oocytes. In this context, we cloned and characterized these two genes of S. frugiperda (SfVg and SfVgR) and evaluated their expression profiles in different developmental stages and tissues. The RNA interference experiment was used to investigate their function in vitellogenesis. The ORF values of SfVg and SfVgR were 5250 and 5445 bp, encoding 1749 and 1815 amino acid residues, respectively. The qRT-PCR results revealed that both SfVg and SfVgR were highly expressed in female adults; SfVg was specifically expressed in the fat body, whereas SfVgR was highly expressed in the ovary. In addition, the depletion of either SfVg or SfVgR hindered oocyte maturation and ovarian development, leading to a significant decrease in fecundity. The present study reveals the importance of SfVg and SfVgR in the vitellogenesis of S. frugiperda, laying a theoretical foundation for the development of pollution-free pest control strategies with SfVg and SfVgR as new targets.

First Report of Alternaria tenuissima Causing Brown Spot Disease of Angelica dahurica in China.

Angelica dahurica (Fisch. ex Hoffm.) is an abundantly cultivated Chinese herbal medicine plant in China with about 4000 hectares grown, the annual production is up to 24,000 tons. The medicinal part of A. dahurica is its root, and mainly function for treat cold, headache, toothache, rhinitis, diabetes, etc. Besides, A. dahurica is also used as a spice in Asia. In September 2018, brown spot was observed on the leaves of A. dahurica in fields of Anguo City, Hebei Province, China. In the field investigated, the incidence of brown spot disease reached 15%. The infected leaves showed brown spots surrounded with pale yellow edge, resulting in withered of the whole leaf. It seriously endangers the growth of A. dahurica, reducing the yield and quality of medicinal materials, even leading to the death of plants. We isolated the pathogen from 10 leaves with same lesions, the small square leaf pieces of approximately 3 to 5 mm were obtained with the sterile scissors from the junction of infected and healthy tissues, sterilized with sodium hypochlorite (10%) for 1 min followed by washing in sterile water for 3 times, then incubated on potato dextrose agar (PDA) plates at 25°C for 4 days. The culture was transferred to new PDA plates and was cultivated in dark at 25°C for 10 days. A total of 3 species of fungi were isolated, and only one fungus species has been found to be able to cause the original pathological characteristics of A. dahurica leaves through the back-grafting experiment. The mycelium was black and began to sporulate after 8 days on PDA media by single spore separation. Multiple spores joined together to form spores chain. The spores were spindle-shaped, yellow to yellow brown, and size ranged from 45 to 55 × 15 to 20 µm (n=50), with zero to three longitudinal septa and one to five transverse septa. For pathogenicity tests, the spore suspension (3.5×105 spores/mL) were inoculated to healthy plants grown in experimental field, the test was repeated four times, and 10 leaves were inoculated in each repetition, and the sterile water was inoculated as the blank control. Inoculated leaves were covered with transparent plastic bags for 24 h to keep humidity. Nine days later, it was found that there were lesions on the leaves inoculated with the pathogen, and the traits were the same as those in the field, while the controls are healthy. The fungus was consistently isolated from the inoculated leaves. The similar isolates were re-isolated from the inoculated and infected leaves and identified as Alternaria tenuissima by DNA sequencing, fulfilling Koch's postulates. Fungal genomic DNA was extracted from 7-day-old culture. PCR amplifications were performed using primers ITS1 / ITS4 and TEFF / TEFR respectively (Takahashi et al. 2006, Du 2008). The nucleotide sequence of PCR products, which have been deposited in Genebank under the accession numbers MN153514 and MN735428, showed 99.8%-100% identity with the corresponding sequences of A. tenuissima (MW194297 and MK415954). In order to further identify the pathogen species, we constructed a phylogenetic tree by combining TEF sequence and ITS sequence to distinguish the relationship between the pathogen and other minor species in the genus Alternaria, the isolate was clustered in the Alternaria clade. Therefore, the pathogen was identified as A. tenuissima based on the morphological characteristics and molecular identification. To our knowledge, this is the first report of A. tenuissima causing leaf spot on A. dahurica in China.

Non-iterative geometric approach for inverse kinematics of redundant lead-module in a radiosurgical snake-like robot.

BACKGROUND: Snake-like robot is an emerging form of serial-link manipulator with the morphologic design of biological snakes. The redundant robot can be used to assist medical experts in accessing internal organs with minimal or no invasion. Several snake-like robotic designs have been proposed for minimal invasive surgery, however, the few that were developed are yet to be fully explored for clinical procedures. This is due to lack of capability for full-fledged spatial navigation. In rare cases where such snake-like designs are spatially flexible, there exists no inverse kinematics (IK) solution with both precise control and fast response. METHODS: In this study, we proposed a non-iterative geometric method for solving IK of lead-module of a snake-like robot designed for therapy or ablation of abdominal tumors. The proposed method is aimed at providing accurate and fast IK solution for given target points in the robot's workspace. n-1 virtual points (VPs) were geometrically computed and set as coordinates of intermediary joints in an n-link module. Suitable joint angles that can place the end-effector at given target points were then computed by vectorizing coordinates of the VPs, in addition to coordinates of the base point, target point, and tip of the first link in its default pose. The proposed method is applied to solve IK of two-link and redundant four-link modules. RESULTS: Both two-link and four-link modules were simulated with Robotics Toolbox in Matlab 8.3 (R2014a). Implementation result shows that the proposed method can solve IK of the spatially flexible robot with minimal error values. Furthermore, analyses of results from both modules show that the geometric method can reach 99.21 and 88.61% of points in their workspaces, respectively, with an error threshold of 1 mm. The proposed method is non-iterative and has a maximum execution time of 0.009 s. CONCLUSIONS: This paper focuses on solving IK problem of a spatially flexible robot which is part of a developmental project for abdominal surgery through minimal invasion or natural orifices. The study showed that the proposed geometric method can resolve IK of the snake-like robot with negligible error offset. Evaluation against well-known methods shows that the proposed method can reach several points in the robot's workspace with high accuracy and shorter computational time, simultaneously.

Effect of Different Host Plants on the Diversity of Gut Bacterial Communities of Spodoptera frugiperda (J. E. Smith, 1797).

Intestinal symbiotic bacteria have formed an interdependent symbiotic relationship with many insect species after long-term coevolution, which plays a critical role in host growth and adaptation. Spodoptera frugiperda (J. E. Smith) is a worldwide significant migratory invasive pest. As a polyphagous pest, S. frugiperda can harm more than 350 plants and poses a severe threat to food security and agricultural production. In this study, 16S rRNA high-throughput sequencing technology was used to analyze the diversity and structure of the gut bacteria of this pest feeding on six diets (maize, wheat, rice, honeysuckle flowers, honeysuckle leaves, and Chinese yam). The results showed that the S. frugiperda fed on rice had the highest bacterial richness and diversity, whereas the larvae fed on honeysuckle flowers had the lowest abundance and diversity of gut bacterial communities. Firmicutes, Actinobacteriota, and Proteobacteria were the most dominant bacterial phyla. PICRUSt2 analysis indicated that most of the functional prediction categories were concentrated in metabolic bacteria. Our results confirmed that the gut bacterial diversity and community composition of S. frugiperda were affected significantly by host diets. This study provided a theoretical basis for clarifying the host adaptation mechanism of S. frugiperda, which also provided a new direction to improve polyphagous pest management strategies.

Molecular Identification and Functional Characterization of Methoprene-Tolerant (Met) and Krüppel-Homolog 1 (Kr-h1) in Harmonia axyridis (Coleoptera: Coccinellidae).

Juvenile hormone (JH) plays a key role in regulating insect reproductive processes. Methoprene-tolerant (Met), as a putative JH receptor, transduces JH signals by activating the transcription factor krüppel homolog 1 (Kr-h1). To understand the effects of Met and Kr-h1 genes on female reproduction of natural enemy insects, the Met and Kr-h1 were identified and analyzed from Harmonia axyridis Pallas (HmMet and HmKr-h1). The HmMet protein belonged to the bHLH-PAS family with bHLH domain, PAS domains, and PAC domain. HmMet mRNA was detected in all developmental stages, and the highest expression was found in the ovaries of female adults. The HmKr-h1 protein had eight C2H2-type zinc finger domains. HmKr-h1 mRNA was highly expressed from day 7 to day 9 of female adults. The tissue expression showed that HmKr-h1 was highly expressed in its wing, leg, and fat body. Knockdown of HmMet and HmKr-h1 substantially reduced the transcription of HmVg1 and HmVg2, inhibited yolk protein deposition, and reduced fecundity using RNA interference. In addition, the preoviposition period was significantly prolonged after dsMet-injection, but there was no significant difference after dsKr-h1-silencing. However, the effect on hatchability results was the opposite. Therefore, we infer that both HmMet and HmKr-h1 are involved in female reproduction of H. axyridis, and their specific functions are different in certain physiological processes. In several continents, H. axyridis are not only beneficial insects, but also invasive pests. This report will provide basis for applying or controlling the H. axyridis.

Molecular Identification and Functional Characterization of Vitellogenin Receptor From Harmonia axyridis (Coleoptera: Coccinellidae).

Vitellogenin receptors (VgRs) have vital roles in reproduction by mediating endocytosis of the vitellogenin (Vg) in oviparous insects. Same as most insect species that possess only one VgR, in this study, a single VgR mRNA (HmVgR) was identified in an important natural enemy ladybeetle, Harmonia axyridis (Pallas). The open reading frame of HmVgR was 5,340 bases encoding a protein of 1,779 amino acids. Bioinformatic analyses showed that HmVgR had conserved domain motifs of low-density lipoprotein receptor family. Based on phylogenetic analysis, HmVgR had highly homologous within the Coleoptera. The transcriptional level of HmVgR was initially detected in the newly emerged female adults, gradually increased from day 3 to day 9, peaked on day 13, and then sharply decreased on day 15. Similar to most insects, HmVgR was expressed specifically in ovarian tissue. Moreover, RNA interference (RNAi) clearly decreased the transcription levels of HmVgR, which blocked the deposition of yolk protein in the ovaries, shortened the ovarian length, and led to negative impacts on reproductive-related parameters (i.e., prolonged preoviposition periods, reduced spawning and depressed hatchability). In sum, these results indicated that HmVgR may be critical for yolk protein deposition of oocytes and can play a key role in reproduction of female adults of H. axyridis. Our results provide conclusive proof for the important roles of HmVgR in fecundity, and establish a basis for further research on its interaction with vitellogenin.

Hybrid Deep Recurrent Neural Networks for Noise Reduction of MEMS-IMU with Static and Dynamic Conditions.

Micro-electro-mechanical system inertial measurement unit (MEMS-IMU), a core component in many navigation systems, directly determines the accuracy of inertial navigation system; however, MEMS-IMU system is often affected by various factors such as environmental noise, electronic noise, mechanical noise and manufacturing error. These can seriously affect the application of MEMS-IMU used in different fields. Focus has been on MEMS gyro since it is an essential and, yet, complex sensor in MEMS-IMU which is very sensitive to noises and errors from the random sources. In this study, recurrent neural networks are hybridized in four different ways for noise reduction and accuracy improvement in MEMS gyro. These are two-layer homogenous recurrent networks built on long short term memory (LSTM-LSTM) and gated recurrent unit (GRU-GRU), respectively; and another two-layer but heterogeneous deep networks built on long short term memory-gated recurrent unit (LSTM-GRU) and a gated recurrent unit-long short term memory (GRU-LSTM). Practical implementation with static and dynamic experiments was carried out for a custom MEMS-IMU to validate the proposed networks, and the results show that GRU-LSTM seems to be overfitting large amount data testing for three-dimensional axis gyro in the static test. However, for X-axis and Y-axis gyro, LSTM-GRU had the best noise reduction effect with over 90% improvement in the three axes. For Z-axis gyroscope, LSTM-GRU performed better than LSTM-LSTM and GRU-GRU in quantization noise and angular random walk, while LSTM-LSTM shows better improvement than both GRU-GRU and LSTM-GRU networks in terms of zero bias stability. In the dynamic experiments, the Hilbert spectrum carried out revealed that time-frequency energy of the LSTM-LSTM, GRU-GRU, and GRU-LSTM denoising are higher compared to LSTM-GRU in terms of the whole frequency domain. Similarly, Allan variance analysis also shows that LSTM-GRU has a better denoising effect than the other networks in the dynamic experiments. Overall, the experimental results demonstrate the effectiveness of deep learning algorithms in MEMS gyro noise reduction, among which LSTM-GRU network shows the best noise reduction effect and great potential for application in the MEMS gyroscope area.

Selection and Evaluation of Reference Genes for qRT-PCR in Spodoptera frugiperda (Lepidoptera: Noctuidae).

As an accurate and convenient technique, the qRT-PCR is always used in the quantitative expression analysis of functional genes. Normalization of the data relies on stable reference genes. The fall armyworm Spodoptera frugiperda (J. E. Smith) is an important invasive and migratory pest that seriously threatens corn production around the world. In this paper, we selected 10 candidate reference genes (18S, AK, RPL10, RPS24, 28S, SOD, ATP, GAPDH, ACT, and a-TUB) and determined their expression levels under different conditions (different developmental stages, various tissues, mating status, hormones, diets, and temperatures). Subsequently, the stability of reference genes was evaluated by four algorithms (Delta Ct method, geNorm, NormFinder, BestKeeper). The optimal combination of reference genes for each treatment was obtained by geNorm. Finally, the comprehensive ranks were determined by the online tool RefFinder. Results showed that the most stable reference genes were SOD, RPL10, and RPS24 for developmental stages, α-TUB, RPL10, and ATP for different tissues, AK, RPL10, and 18S for mating status, 18S and AK under hormone treatment, 18S, RPL10, and SOD under diet treatment, RPL10, 18S, and RPS24 under temperature treatment. This study confirmed recent data on a few reference genes and provided an evaluation of a number of additional reference genes of S. frugiperda under various conditions.

Random Error Reduction Algorithms for MEMS Inertial Sensor Accuracy Improvement-A Review.

Research and industrial studies have indicated that small size, low cost, high precision, and ease of integration are vital features that characterize microelectromechanical systems (MEMS) inertial sensors for mass production and diverse applications. In recent times, sensors like MEMS accelerometers and MEMS gyroscopes have been sought in an increased application range such as medical devices for health care to defense and military weapons. An important limitation of MEMS inertial sensors is repeatedly documented as the ease of being influenced by environmental noise from random sources, along with mechanical and electronic artifacts in the underlying systems, and other random noise. Thus, random error processing is essential for proper elimination of artifact signals and improvement of the accuracy and reliability from such sensors. In this paper, a systematic review is carried out by investigating different random error signal processing models that have been recently developed for MEMS inertial sensor precision improvement. For this purpose, an in-depth literature search was performed on several databases viz., Web of Science, IEEE Xplore, Science Direct, and Association for Computing Machinery Digital Library. Forty-nine representative papers that focused on the processing of signals from MEMS accelerometers, MEMS gyroscopes, and MEMS inertial measuring units, published in journal or conference formats, and indexed on the databases within the last 10 years, were downloaded and carefully reviewed. From this literature overview, 30 mainstream algorithms were extracted and categorized into seven groups, which were analyzed to present the contributions, strengths, and weaknesses of the literature. Additionally, a summary of the models developed in the studies was presented, along with their working principles viz., application domain, and the conclusions made in the studies. Finally, the development trend of MEMS inertial sensor technology and its application prospects were presented.

Motion and Trajectory Constraints Control Modeling for Flexible Surgical Robotic Systems.

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.

Learning-based Parameter Estimation for Hysteresis Modeling in Robotic Catheterization.

In the last half decade, nearly 31% of annual global deaths are linked to cardiovascular diseases. Thus, robotic catheterizations are recently proposed for interventions of conditions such as aneurism or atherosclerosis formed along vascular paths leading to the heart. However, existence of mild to strong hysteresis while navigating unactuated catheters with the current robotic systems inhibits autonomous control for vascular surgery. Thus, immersion of surgeons remains high with most of their time spent on steering the catheter in-and- out of the vessels. In this study, an autoregressive nonlinear neural network model is adapted for parameterization of vital causal factors of hysteresis during robotic catheterization. Crucial for autonomous control, hysteretic behaviors of endovascular tool are modeled while suitable values are estimated and analyzed for five contributory factors. The network model is validated with hysteresis data we obtained from a two degree-of-freedom robotic system and an unactuated catheter. Result validation shows accurate description of the hysteresis profile recorded during catheterization trials with a vascular phantom model.

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

Recently, snake-like robots are proposed to assist experts during medical procedures on internal organs via natural orifices. Despite their well-spelt advantages, applications in radiosurgery is still hindered by absence of suitable designs required for spatial navigations within clustered and confined parts of human body, and inexistence of precise and fast inverse kinematics (IK) models. In this study, a deeply-learnt damped least squares method is proposed for solving IK of spatial snake-like robot. The robot's model consists of several modules, and each module has a pair of serial-links connected with orthogonal twists. For precise control of the robot's end-effector, damped least-squares approach is used to minimize error magnitude in a function modeled over analytical Jacobian of the robot. This is iteratively done until an apt joint vector needed to converge the robot to desired positions is obtained. For fast control and singularity avoidance, a deep network is built for prediction of unique damping factor required for each target point in the robot's workspace. The deep network consists of 11 x 15 array of neurons at the hidden layer, and deeply-learnt with a huge dataset of 877,500 data points generated from workspace of the snake robot. Implementation results for both simulated and actual prototype of an eight-link model of the robot show the effectiveness of the proposed IK method. With error tolerance of 0.01 mm, the proposed method has a very high reachability measure of 91.59% and faster mean execution time of 9.20 (±16.92) ms for convergence. In addition, the method requires an average of 33.02 (±39.60) iterations to solve the IK problem. Hence, approximately 3.6 iterations can be executed in 1 ms. Evaluation against popularly used IK methods shows that the proposed method has very good performance in terms of accuracy and speed, simultaneously.