Pub Date : 2023-12-04DOI: 10.1109/ROBIO58561.2023.10354697
Jingwen Wei, Siyuan Li
This paper presents a novel hybrid algorithm aimed at optimizing the planning of forest fire rescue routes. The proposed method utilizes a hierarchical architecture to ensure safe navigation deployment, particularly in environments that are either unknown or only partially known. The observation layer effectively deploys a comprehensive set of feasible navigation points through the utilization of global path planning techniques. Subsequently, the execution layer takes charge of executing these navigational actions. To further enhance safety, the decision layer assesses whether the unmanned aerial vehicle (UAV) requires local obstacle avoidance strategies. Furthermore, an additional decision regarding replanning is incorporated into the decision layer, addressing the potential risks associated with dynamic avoidance approaches. This consideration effectively mitigates issues like being trapped in a perpetual loop or encountering path-finding challenges.
{"title":"A hybrid algorithm of UAV path planning for rescue in bushfire environments","authors":"Jingwen Wei, Siyuan Li","doi":"10.1109/ROBIO58561.2023.10354697","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354697","url":null,"abstract":"This paper presents a novel hybrid algorithm aimed at optimizing the planning of forest fire rescue routes. The proposed method utilizes a hierarchical architecture to ensure safe navigation deployment, particularly in environments that are either unknown or only partially known. The observation layer effectively deploys a comprehensive set of feasible navigation points through the utilization of global path planning techniques. Subsequently, the execution layer takes charge of executing these navigational actions. To further enhance safety, the decision layer assesses whether the unmanned aerial vehicle (UAV) requires local obstacle avoidance strategies. Furthermore, an additional decision regarding replanning is incorporated into the decision layer, addressing the potential risks associated with dynamic avoidance approaches. This consideration effectively mitigates issues like being trapped in a perpetual loop or encountering path-finding challenges.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"88 8","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139186731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-04DOI: 10.1109/ROBIO58561.2023.10354911
Shumpei Tokuda, Masaki Yamakita, Hiroyuki Oyama, Rin Takano
We propose a new nonlinear optimization-based method for signal temporal logic (STL) specification with uncertain external events. STL provides a simple way to express complex task specifications for robotic and cyber-physical systems. Event-based STL is an extension of STL and can describe the response to external events, which should be considered in practical applications. We define smooth robustness functions for event-based STL specifications and formulate a nonlinear optimization problem for event-based STL specifications. Our method introduces augmented continuous variables for external events into the optimization problem to generate robust trajectories for uncertain external events that may occur. We demonstrate the effectiveness of our method through numerical simulations.
{"title":"Robust Signal Temporal Logic-based Planning for Uncertain External Events","authors":"Shumpei Tokuda, Masaki Yamakita, Hiroyuki Oyama, Rin Takano","doi":"10.1109/ROBIO58561.2023.10354911","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354911","url":null,"abstract":"We propose a new nonlinear optimization-based method for signal temporal logic (STL) specification with uncertain external events. STL provides a simple way to express complex task specifications for robotic and cyber-physical systems. Event-based STL is an extension of STL and can describe the response to external events, which should be considered in practical applications. We define smooth robustness functions for event-based STL specifications and formulate a nonlinear optimization problem for event-based STL specifications. Our method introduces augmented continuous variables for external events into the optimization problem to generate robust trajectories for uncertain external events that may occur. We demonstrate the effectiveness of our method through numerical simulations.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"88 5","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139186733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-04DOI: 10.1109/ROBIO58561.2023.10354826
Hao Hu, Letian Qian, Zhanhao Xu, Xin Luo
The running of animals and humans often exhibits a spring-like leg behavior, which is abstractly explained by the Spring-Loaded Inverted Pendulum (SLIP) model. However, such an equivalent model neglects the nonlinear characteristics generated by the spring-like behavior localized at the joint level, leading to a substantial difference from those in the real system when analyzing locomotion stability and energy efficiency. The segmented leg model introduces the stiffness and rest angle of the virtual torsion spring at the joint into the dynamics to demonstrate the nonlinear relationship between the leg force and the leg compression. Due to the introduction of multiple parameters, it is of great significance to determine the optimal parameter combination. In this paper, we present a method to analyze the effects of the model parameters on the self-stability and energy efficiency. The nonlinear relationship between leg force and leg compression, and the hybrid dynamics of a two-segmented leg model are built, the apex return map is introduced to set up the self-stable constraints based on passive dynamics, and the effects of model parameters on the running energy efficiency are investigated via numerical simulation. The simulation results reveal that the highest energy efficiency is achieved when the stiffness is set to be the maximum value allowed and achievable, and the target running pattern is located at the fixed point corresponding to the largest angle to attack. The methodology to determine the model parameters is concluded based on the simulation results.
{"title":"Analysis of Stability and Energy Efficiency of Legged Running Based on the Two-Segmented Leg Model","authors":"Hao Hu, Letian Qian, Zhanhao Xu, Xin Luo","doi":"10.1109/ROBIO58561.2023.10354826","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354826","url":null,"abstract":"The running of animals and humans often exhibits a spring-like leg behavior, which is abstractly explained by the Spring-Loaded Inverted Pendulum (SLIP) model. However, such an equivalent model neglects the nonlinear characteristics generated by the spring-like behavior localized at the joint level, leading to a substantial difference from those in the real system when analyzing locomotion stability and energy efficiency. The segmented leg model introduces the stiffness and rest angle of the virtual torsion spring at the joint into the dynamics to demonstrate the nonlinear relationship between the leg force and the leg compression. Due to the introduction of multiple parameters, it is of great significance to determine the optimal parameter combination. In this paper, we present a method to analyze the effects of the model parameters on the self-stability and energy efficiency. The nonlinear relationship between leg force and leg compression, and the hybrid dynamics of a two-segmented leg model are built, the apex return map is introduced to set up the self-stable constraints based on passive dynamics, and the effects of model parameters on the running energy efficiency are investigated via numerical simulation. The simulation results reveal that the highest energy efficiency is achieved when the stiffness is set to be the maximum value allowed and achievable, and the target running pattern is located at the fixed point corresponding to the largest angle to attack. The methodology to determine the model parameters is concluded based on the simulation results.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"99 3","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139186754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-04DOI: 10.1109/ROBIO58561.2023.10354675
Annika Guez, Saksham Dhawan, Ravi Vaidyanathan
For unilateral pathologies, effective rehabilitation relies on the use of a customised trajectory in order for the user to relearn a natural and symmetrical gait. In recent years, lower-limb exoskeletons have seen a growing interest due to their capacity to provide support and facilitate repetitive exercises while correcting the user’s motion. However, in the context of robotic-assisted locomotion, the investigated trajectory models tend to rely on generating standardised walking patterns that lack step-specific customisation, and therefore do not account for the dynamic variations of natural gait.This paper investigates the viability of an echo-based approach for trajectory generation, which centres around the dynamic relabelling of a time-invariant reference trajectory, based on the motion of the contralateral leg. The presented cascaded network combines (1) a classifier that determines the gait phase performed by the sound leg and updates the reference trajectory accordingly, with (2) a regressor that uses electromyography inputs from the investigated leg to predict the gait cycle percentage performed, and provide the associated knee angle based on the dynamic reference.This trajectory generation framework was evaluated on 6 able-bodied subjects, using both steady-state and transient speeds. Despite some discrepancies in the range of motion, the produced knee angle trajectory strongly resembles the experimentally captured ones for both conditions, with an average mapping Root Mean Squared Error across subjects of 4.62°±0.39° for steady-state and 5.88°±1.83°for transient speeds. This proof-of-concept implementation demonstrates the potential of an echo-based approach for personalised dynamic trajectory generation in unilateral exoskeleton applications.
{"title":"Echo-based dynamic trajectory generation for customised unilateral exoskeleton applications","authors":"Annika Guez, Saksham Dhawan, Ravi Vaidyanathan","doi":"10.1109/ROBIO58561.2023.10354675","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354675","url":null,"abstract":"For unilateral pathologies, effective rehabilitation relies on the use of a customised trajectory in order for the user to relearn a natural and symmetrical gait. In recent years, lower-limb exoskeletons have seen a growing interest due to their capacity to provide support and facilitate repetitive exercises while correcting the user’s motion. However, in the context of robotic-assisted locomotion, the investigated trajectory models tend to rely on generating standardised walking patterns that lack step-specific customisation, and therefore do not account for the dynamic variations of natural gait.This paper investigates the viability of an echo-based approach for trajectory generation, which centres around the dynamic relabelling of a time-invariant reference trajectory, based on the motion of the contralateral leg. The presented cascaded network combines (1) a classifier that determines the gait phase performed by the sound leg and updates the reference trajectory accordingly, with (2) a regressor that uses electromyography inputs from the investigated leg to predict the gait cycle percentage performed, and provide the associated knee angle based on the dynamic reference.This trajectory generation framework was evaluated on 6 able-bodied subjects, using both steady-state and transient speeds. Despite some discrepancies in the range of motion, the produced knee angle trajectory strongly resembles the experimentally captured ones for both conditions, with an average mapping Root Mean Squared Error across subjects of 4.62°±0.39° for steady-state and 5.88°±1.83°for transient speeds. This proof-of-concept implementation demonstrates the potential of an echo-based approach for personalised dynamic trajectory generation in unilateral exoskeleton applications.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"86 10","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139186769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-04DOI: 10.1109/ROBIO58561.2023.10354774
Shah Darshankumar Rajendrakumar, A. Kakogawa, Shugen Ma
This paper presents the design of an underwater snake-like robot featuring four fully submersible joints and verifying its primary underwater properties. The actuators that drive these joints are designed to focus on minimal friction, have a lubricant-free gear reducer, and have no waterproof sealing, making them suitable for direct exposure to underwater experiments. The paper thoroughly discusses the efficiency and command/actual torque measurement of these actuators, the design of the snake robot, and the primary underwater verification. The ultimate objective of this snake robot is to enable it to engage in interactive tasks that require direct mechanical interaction with the underwater surroundings. The execution of various tasks with this snake robot remains part of future work. The robot demonstrates serpentine and eel-like locomotion in the underwater environment, showcasing its adaptability and potential for various applications in underwater environment.
{"title":"An Underwater Snake Robot that Does Not Consider Actuators’ Waterproof: Design and Primary Experiments","authors":"Shah Darshankumar Rajendrakumar, A. Kakogawa, Shugen Ma","doi":"10.1109/ROBIO58561.2023.10354774","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354774","url":null,"abstract":"This paper presents the design of an underwater snake-like robot featuring four fully submersible joints and verifying its primary underwater properties. The actuators that drive these joints are designed to focus on minimal friction, have a lubricant-free gear reducer, and have no waterproof sealing, making them suitable for direct exposure to underwater experiments. The paper thoroughly discusses the efficiency and command/actual torque measurement of these actuators, the design of the snake robot, and the primary underwater verification. The ultimate objective of this snake robot is to enable it to engage in interactive tasks that require direct mechanical interaction with the underwater surroundings. The execution of various tasks with this snake robot remains part of future work. The robot demonstrates serpentine and eel-like locomotion in the underwater environment, showcasing its adaptability and potential for various applications in underwater environment.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"85 7","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139186801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-04DOI: 10.1109/ROBIO58561.2023.10354647
Ma Zheng, Li Kai, Xiao-Guang Hu
In recent years, biomimetic robotics has emerged as a promising field that draws inspiration from nature to develop innovative and efficient robots. In this study, we have designed a biorobot capable of crawling and barrier-crossing, inspired by the walking gaits of crabs. Firstly, we analyzed the motion of an individual crab leg to determine the required degrees of freedom for crawling and barrier-crossing. Then, we utilize the screw theory to synthesize the mechanism of a single branch. Finally, we select a suitable parallel mechanism configuration for this research. Simulation analysis is conducted to test the variations in actuation at different driving points under various pose states. We observe stability in changes in driving points with respect to the retraction angle of the leg, indicating excellent obstacle overcoming capabilities possessed by this robot.
{"title":"The virtual prototype design and simulation of crab walking gaits inspired crawling and barrier-crossing parallel mechanism","authors":"Ma Zheng, Li Kai, Xiao-Guang Hu","doi":"10.1109/ROBIO58561.2023.10354647","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354647","url":null,"abstract":"In recent years, biomimetic robotics has emerged as a promising field that draws inspiration from nature to develop innovative and efficient robots. In this study, we have designed a biorobot capable of crawling and barrier-crossing, inspired by the walking gaits of crabs. Firstly, we analyzed the motion of an individual crab leg to determine the required degrees of freedom for crawling and barrier-crossing. Then, we utilize the screw theory to synthesize the mechanism of a single branch. Finally, we select a suitable parallel mechanism configuration for this research. Simulation analysis is conducted to test the variations in actuation at different driving points under various pose states. We observe stability in changes in driving points with respect to the retraction angle of the leg, indicating excellent obstacle overcoming capabilities possessed by this robot.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"106 6","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139186820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-04DOI: 10.1109/ROBIO58561.2023.10354757
Daming Nie, Anhuan Xie, Lingyu Kong, Yu Zhang, Gang Zheng, Yili Fu, Jason Gu
Human bones have formed the preferred configuration for high-strength and lightweight after long-time evolution. Taking human’s longest and strongest bone - the femur - as an example, it is consist of two characteristic layers, i.e. the substantia compacta and the substantia spongiosd. This article innovatively imitates the structural characteristics of human femur, the thigh of humanoid robot is designed in form of "variable thickness shell + variable density lattice". The thickness of shell and the density of lattice are adjusted by the initial stress distribution individually. Results show that the weight of shell and lattice of the thigh structure can be reduced by 20% under reasonable mapping relationship of "stress - shell thickness" and "stress - lattice rod diameter", while the structural stiffness meets the application requirements. Finally, the limiting factors of the "variable thickness shell + variable density lattice" structure designing approach are analyzed, and potential measures for optimizing the design method of the humanoid robot thigh in the future are described.
{"title":"Research on Biomimetic Design Methods for Humanoid Robot Thigh*","authors":"Daming Nie, Anhuan Xie, Lingyu Kong, Yu Zhang, Gang Zheng, Yili Fu, Jason Gu","doi":"10.1109/ROBIO58561.2023.10354757","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354757","url":null,"abstract":"Human bones have formed the preferred configuration for high-strength and lightweight after long-time evolution. Taking human’s longest and strongest bone - the femur - as an example, it is consist of two characteristic layers, i.e. the substantia compacta and the substantia spongiosd. This article innovatively imitates the structural characteristics of human femur, the thigh of humanoid robot is designed in form of \"variable thickness shell + variable density lattice\". The thickness of shell and the density of lattice are adjusted by the initial stress distribution individually. Results show that the weight of shell and lattice of the thigh structure can be reduced by 20% under reasonable mapping relationship of \"stress - shell thickness\" and \"stress - lattice rod diameter\", while the structural stiffness meets the application requirements. Finally, the limiting factors of the \"variable thickness shell + variable density lattice\" structure designing approach are analyzed, and potential measures for optimizing the design method of the humanoid robot thigh in the future are described.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"84 5","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139186834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-04DOI: 10.1109/ROBIO58561.2023.10354557
A. Klimchik
The paper deals with the comparison analysis of build-in and model-based control strategies for robots with double encoders. Particular attention is paid to the efficiency evaluation of the related compliance error compensation techniques. Three different model-based control strategies were examined. It was shown that reduced stiffness model-based and joint-compliance-ratio-based strategies could compensate twice as much as built-in feedback control based on the secondary encoder and reduce 77% of positioning errors. The complete stiffness model achieved a 97% compliance error compensation level and regardless of its complexity, it is a reasonable approach for the robots involved in high-accuracy contact applications.
{"title":"Comparison of compliance error compensation approaches for robotic manipulators with double encoders","authors":"A. Klimchik","doi":"10.1109/ROBIO58561.2023.10354557","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354557","url":null,"abstract":"The paper deals with the comparison analysis of build-in and model-based control strategies for robots with double encoders. Particular attention is paid to the efficiency evaluation of the related compliance error compensation techniques. Three different model-based control strategies were examined. It was shown that reduced stiffness model-based and joint-compliance-ratio-based strategies could compensate twice as much as built-in feedback control based on the secondary encoder and reduce 77% of positioning errors. The complete stiffness model achieved a 97% compliance error compensation level and regardless of its complexity, it is a reasonable approach for the robots involved in high-accuracy contact applications.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"8 3","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139186843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-04DOI: 10.1109/ROBIO58561.2023.10354927
You Wang, Ziyi Zou, Ziang Zhang, Xiaoqing Guan, Boyu Lin, Xiang Li, Guang Li
In this paper, we propose an efficient trajectory planning algorithm with path smoothing based on the Bézier curve with curvature constraints and piecewise-jerk speed-time optimization. We use hybrid A* to generate a rough path and construct a safe corridor by inflating the path. After that, we formulate the smooth problem as a nonlinear programming(NLP) with piecewise Bézier curves. Since the curvature constraints for Bézier curves are difficult, we employ quartic Bézier Curves with special forms and compute the closed-form solution for the maximum curvature to simplify the representation of the maximum curvature. By using the special Bézier curves, we realize the gear shifts and easily guarantee the security, continuity, and feasibility of the path. Meanwhile, we add time variables based on PJSO, improving the quality of trajectory within an acceptable increase in time, making the allocation of time and speed better. Simulation and real-world experiments with a car-like robot in various environments confirm that our algorithm can generate a smooth, feasible, and high-quality trajectory for robots.
{"title":"Autonomous Trajectory Planning Based on Bézier Curve with Curvature Constraints and Piecewise-Jerk Speed-Time Optimization","authors":"You Wang, Ziyi Zou, Ziang Zhang, Xiaoqing Guan, Boyu Lin, Xiang Li, Guang Li","doi":"10.1109/ROBIO58561.2023.10354927","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354927","url":null,"abstract":"In this paper, we propose an efficient trajectory planning algorithm with path smoothing based on the Bézier curve with curvature constraints and piecewise-jerk speed-time optimization. We use hybrid A* to generate a rough path and construct a safe corridor by inflating the path. After that, we formulate the smooth problem as a nonlinear programming(NLP) with piecewise Bézier curves. Since the curvature constraints for Bézier curves are difficult, we employ quartic Bézier Curves with special forms and compute the closed-form solution for the maximum curvature to simplify the representation of the maximum curvature. By using the special Bézier curves, we realize the gear shifts and easily guarantee the security, continuity, and feasibility of the path. Meanwhile, we add time variables based on PJSO, improving the quality of trajectory within an acceptable increase in time, making the allocation of time and speed better. Simulation and real-world experiments with a car-like robot in various environments confirm that our algorithm can generate a smooth, feasible, and high-quality trajectory for robots.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"90 11","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139186904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-04DOI: 10.1109/ROBIO58561.2023.10354987
Yuchuan Yang, Manjia Su, Yisheng Guan, Wangcheng Chen
Most control methods for soft robots are developed based on kinematic models derived from deformation and force analysis. However, due to the non-linearity and uncertainty of soft robotic structure, it is difficult to establish accurate models, leaving a great gap in the precise control of soft robots. Recent research has shown that machine learning provides a highly effective solution. In this work, we propose a back-propagation neural network based on particle swarm optimization algorithm to establish the surrogate kinematics of a airbag-type soft actuator. Using the motion data of the soft actuator to train the network model, the corresponding relationship between the soft actuator and the end position can be obtained. The results show that the surrogate model has a good prediction effect, and the average relative error of the model is 6.4%, enabling control the motion of the soft actuator accurately enough.
{"title":"Motion Control Utilizing Surrogate Model for A Soft Actuator Driven by Airbag-typed Cells","authors":"Yuchuan Yang, Manjia Su, Yisheng Guan, Wangcheng Chen","doi":"10.1109/ROBIO58561.2023.10354987","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354987","url":null,"abstract":"Most control methods for soft robots are developed based on kinematic models derived from deformation and force analysis. However, due to the non-linearity and uncertainty of soft robotic structure, it is difficult to establish accurate models, leaving a great gap in the precise control of soft robots. Recent research has shown that machine learning provides a highly effective solution. In this work, we propose a back-propagation neural network based on particle swarm optimization algorithm to establish the surrogate kinematics of a airbag-type soft actuator. Using the motion data of the soft actuator to train the network model, the corresponding relationship between the soft actuator and the end position can be obtained. The results show that the surrogate model has a good prediction effect, and the average relative error of the model is 6.4%, enabling control the motion of the soft actuator accurately enough.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"90 10","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139186905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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