Tensegrity structures,embodying the principles of continuous tensioning and discrete compression,have emerged as fundamental frameworks in locomotive soft robotics for navigating uneven and unpredictable environments,...Tensegrity structures,embodying the principles of continuous tensioning and discrete compression,have emerged as fundamental frameworks in locomotive soft robotics for navigating uneven and unpredictable environments,owing to their flexible and resilient traits.By means of a straightforward and cost-effective method to achieve structure-driven,vibration-driven tensegrity shows great potential,particularly in tasks demanding random exploration.However,the design guidance for vibration-driven tensegrity and their performance evaluation in unstructured terrain remain unrevealed due to the complex dynamics of the structure.This paper presents a small six-bar tensegrity robot,driven by wireless vibration motors,designed for deployment in disaster rescue and search scenarios.Finite element simulation is used to investigate how structural characteristics,excitation parameters,and the arrangement of motors affect the kinematic performance of this tensegrity system.A prototype of the six-bar tensegrity robot with three motors located on the lower ends of the three lower struts is designed and manufactured after the numerical simulations.A simple control policy which adjusts the motion of the tensegrity robot by turning on or off the motors on different locations is proposed.The prototype with and without the control policy is tested in man-made environments of various complexity.It shows that the ability and efficiency of the tensegrity robot in exploring unstructured environments is significantly enhanced by the proposed control policy.It is believed that the potential of the vibration-driven tensegrity robot could be further exploited by integrating multi-source sensors and more intelligent control policies.展开更多
The principal objective of autonomous navigation involves terrain traversability analysis,where traversability refers to the suitability of a given terrain for driving over.It is difficult to infer the traversability ...The principal objective of autonomous navigation involves terrain traversability analysis,where traversability refers to the suitability of a given terrain for driving over.It is difficult to infer the traversability cost from the semantic types or geometric properties of the terrain independently.Robots may develop a false perception of high grass and rugged dirt.To address these challenges,this paper proposes a method for local traversability map generation,which uses onboard LiDAR and cameras to generate local traversability maps.One of the key ideas to achieve this is to build the interaction between the geometric properties and the types of terrain.This relationship represents the sensitivity of traversability to geometry under certain types of terrain,and it will be used in conjunction with semantics and geometry to reason about traversability.Further,to prevent side or longitudinal slipping that exceeds the capacity of the traffic system,vehicle classes and design factors are also incorporated into the calculation of traversability costs.Real-world experimental results demonstrate that the proposed method can generate traversability maps in unstructured environments.Ablation studies substantiate the method's efficacy.Compared to existing methods,our approach provides more reasonable analysis results when dealing with complex environments featuring diverse terrains.展开更多
Snake robots have great potential for exploring and operating in challenging unstructured environments,such as rubble,caves,and narrow pipelines.However,due to the complexity and unpredictability of unstructured envir...Snake robots have great potential for exploring and operating in challenging unstructured environments,such as rubble,caves,and narrow pipelines.However,due to the complexity and unpredictability of unstructured environments,designing a controller that can achieve adaptive motion is crucial.This paper proposes a self-adaptive torque-based rolling controller for snake robots,enabling compliant motion in unstructured environments.First,a controller is designed to modify the torque of each motor by focusing on the different motion states of the rolling gait.Second,an experimental platform is established for snake robots to verify the effectiveness of the controller.Finally,a series of rolling experiments are conducted using the torque-based rolling controller.In conclusion,the self-adaptive torque-based rolling controller enhances snake robot adaptability and mobility.展开更多
With the advancement of deep learning in the automotive domain,more and more researchers are focusing on autonomous driving.Among these tasks,free space detection is particularly crucial.Currently,many model-based app...With the advancement of deep learning in the automotive domain,more and more researchers are focusing on autonomous driving.Among these tasks,free space detection is particularly crucial.Currently,many model-based approaches have achieved autonomous driving on well-structured urban roads,but these efforts primarily focus on urban road environments.In contrast,there are fewer deep learningmethods specifically designed for off-road traversable area detection,and their effectiveness is not yet satisfactory.This is because detecting traversable areas in complex outdoor environments poses significant challenges,and current methods often rely on single-image inputs,which do not align with contemporary multimodal approaches.Therefore,in this study,we propose a CFH-Net model for off-road traversable area detection.This model employs a Transformer architecture to enhance its capability of capturing global information.For multimodal feature extraction and fusion,we integrate the CM-FRM module for feature extraction and introduce the novel FFX module for feature fusion,thereby improving the perception capability of autonomous vehicles on unstructured roads.To address upsampling,we propose a new convolution precorrection method to reduce model parameters and computational complexity while enhancing the model’s ability to capture complex features.Finally,we conducted experiments on the ORFD off-road dataset and achieved outstanding results.展开更多
A novel three-module robot has been introduced. It can change its configuration to adapt to the uneven terrain and to improve its tipover stability. This three-module tracked robot has three kinds of symmetry configur...A novel three-module robot has been introduced. It can change its configuration to adapt to the uneven terrain and to improve its tipover stability. This three-module tracked robot has three kinds of symmetry configuration. They are line type, triangle type, and row type. After the factors and the countermeasures of mobile robot＇s tipover problem are analyzed, stability pyramid and tipover stabil-ity index are proposed to globally determinate the mobile robot＇s static stability and dynamic stability. The shape shifting robot is tested by this technique under the combined disturbance of pitch, roll and yaw in simulation. The simulation result shows that this technique is effective for the analysis of mobile robot＇s tipover stability, especially for the reconfigurable or shape shifting modular robot. Experiments on three symmetry configurations are made under unstructured environments. The environment experiment shows the same result as that of the simulation that the triangle type configuration has the best stability. Both simulation and experiment provide a valid reference for the reconfigurable robot＇s potential application.展开更多
For safety reasons,in the automated dispensing medicines process,robots and humans cooperate to accomplish the task of drug sorting and distribution.In this dynamic unstructured environment,such as a humanrobot collab...For safety reasons,in the automated dispensing medicines process,robots and humans cooperate to accomplish the task of drug sorting and distribution.In this dynamic unstructured environment,such as a humanrobot collaboration scenario,the safety of human,robot,and equipment in the environment is paramount.In this work,a practical and effective robot motion planning method is proposed for dynamic unstructured environments.To figure out the problems of blind zones of single depth sensor and dynamic obstacle avoidance,we first propose a method for establishing offline mapping and online fusion of multi-sensor depth images and 3D grids of the robot workspace,which is used to determine the occupation states of the 3D grids occluded by robots and obstacles and to conduct real-time estimation of the minimum distance between the robot and obstacles.Then,based on the reactive control method,the attractive and repulsive forces are calculated and transformed into robot joint velocities to avoid obstacles in real time.Finally,the robot’s dynamic obstacle avoidance ability is evaluated on an experimental platform with a UR5 robot and two KinectV2 RGB-D sensors,and the effectiveness of the proposed method is verified.展开更多
Abstract： The supervised teleoperation control is presented for a mobile robot to implement the tasks by using fuzzy logic. The teleoperation control system includes joystick based user interaction mechanism, the hig...Abstract： The supervised teleoperation control is presented for a mobile robot to implement the tasks by using fuzzy logic. The teleoperation control system includes joystick based user interaction mechanism, the high level instruction set and fuzzy logic behaviors integrated in a supervised autonomy teleoperation control system for indoor navigation. These behaviors include left wall following, right wall following, turn left, turn right, left obstacle avoidance, right obstacle avoidance and corridor following based on ultrasonic range finders data. The robot compares the instructive high level command from the operator and relays back a suggestive signal back to the operator in case of mismatch between environment and instructive command. This strategy relieves the operator＇s cognitive burden, handle unforeseen situations and uncertainties of environment autonomously. The effectiveness of the proposed method for navigation in an unstructured environment is verified by experiments conducted on a mobile robot equipped with only ultrasonic range finders for environment sensing.展开更多
An algorithm is proposed for scheduling dependent tasks in time-varying heterogeneous multiprocessor systems, in which computational power and links between processors are allowed to change over time. Link contention ...An algorithm is proposed for scheduling dependent tasks in time-varying heterogeneous multiprocessor systems, in which computational power and links between processors are allowed to change over time. Link contention is considered in the multiprocessor scheduling problem. A linear switching-state space-modeling paradigm is introduced to enable theoretical analysis from a system engineering perspective. Theoretical analysis of this model shows its robustness against changes in processing power and link failure. The proposed algorithm uses a fuzzy decision-making procedure to handle changes in the multiprocessor system. The efficiency of the proposed algorithm is illustrated by several random experiments and comparison against a recent benchmark approach. The results show up to 18% average improvement in makespan, especially for larger scale systems.展开更多
In the complex orchard environment,precise picking point localization is crucial for the automation of fruit picking robots.However,existing methods are prone to positioning errors when dealing with complex scenarios ...In the complex orchard environment,precise picking point localization is crucial for the automation of fruit picking robots.However,existing methods are prone to positioning errors when dealing with complex scenarios such as short peduncles,partial occlusion,or complete misidentification,which can affect the actual work efficiency of the fruit picking robot.This study proposes an enhanced picking point localization method based on semantic reasoning for complex picking scenarios in vineyard.It innovatively designs three modules:the semantic reasoning module(SRM),the ROI threshold adjustment strategy(RTAS),and the picking point location optimization module(PPOM).The SRM is applied to handle the scenarios of grape peduncles being obstructed by obstacles,partial misidentification of peduncles,and complete misidentification of peduncles.The RTAS addresses the issue of low and short peduncles during the picking process.Finally,the PPOM optimizes the final position of the picking point,allowing the robotic arm to perform the picking operation with greater flexibility.Experimental results show that SegFormer achieves an mIoU(mean Intersection over Union)of 84.54%,with B_IoU and P_IoU reaching 73.90%and 75.63%,respectively.Additionally,the success rate of the improved fruit picking point localization algorithm reached 94.96%,surpassing the baseline algorithm by 8.12%.The algorithm's average processing time is 0.5428±0.0063 s,meeting the practical requirements for real-time picking.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.52178175 and 52108182)the National Natural Science Foundation of Zhejiang Province(Grant No.LZ23E080003).
文摘Tensegrity structures,embodying the principles of continuous tensioning and discrete compression,have emerged as fundamental frameworks in locomotive soft robotics for navigating uneven and unpredictable environments,owing to their flexible and resilient traits.By means of a straightforward and cost-effective method to achieve structure-driven,vibration-driven tensegrity shows great potential,particularly in tasks demanding random exploration.However,the design guidance for vibration-driven tensegrity and their performance evaluation in unstructured terrain remain unrevealed due to the complex dynamics of the structure.This paper presents a small six-bar tensegrity robot,driven by wireless vibration motors,designed for deployment in disaster rescue and search scenarios.Finite element simulation is used to investigate how structural characteristics,excitation parameters,and the arrangement of motors affect the kinematic performance of this tensegrity system.A prototype of the six-bar tensegrity robot with three motors located on the lower ends of the three lower struts is designed and manufactured after the numerical simulations.A simple control policy which adjusts the motion of the tensegrity robot by turning on or off the motors on different locations is proposed.The prototype with and without the control policy is tested in man-made environments of various complexity.It shows that the ability and efficiency of the tensegrity robot in exploring unstructured environments is significantly enhanced by the proposed control policy.It is believed that the potential of the vibration-driven tensegrity robot could be further exploited by integrating multi-source sensors and more intelligent control policies.
基金supported by National Natural Science Foundations of China(Grant No.52205047 and No.52175037)China postdoctoral Science Foundations(Grant No.BX20220379 and No.2021M700422)Frontier Cross Project(2024CX11006).
文摘The principal objective of autonomous navigation involves terrain traversability analysis,where traversability refers to the suitability of a given terrain for driving over.It is difficult to infer the traversability cost from the semantic types or geometric properties of the terrain independently.Robots may develop a false perception of high grass and rugged dirt.To address these challenges,this paper proposes a method for local traversability map generation,which uses onboard LiDAR and cameras to generate local traversability maps.One of the key ideas to achieve this is to build the interaction between the geometric properties and the types of terrain.This relationship represents the sensitivity of traversability to geometry under certain types of terrain,and it will be used in conjunction with semantics and geometry to reason about traversability.Further,to prevent side or longitudinal slipping that exceeds the capacity of the traffic system,vehicle classes and design factors are also incorporated into the calculation of traversability costs.Real-world experimental results demonstrate that the proposed method can generate traversability maps in unstructured environments.Ablation studies substantiate the method's efficacy.Compared to existing methods,our approach provides more reasonable analysis results when dealing with complex environments featuring diverse terrains.
基金supported by the National Natural Science Foundation of China(62072335)Fundamental Research Funds for the Central Universities,China(buctrc202215).
文摘Snake robots have great potential for exploring and operating in challenging unstructured environments,such as rubble,caves,and narrow pipelines.However,due to the complexity and unpredictability of unstructured environments,designing a controller that can achieve adaptive motion is crucial.This paper proposes a self-adaptive torque-based rolling controller for snake robots,enabling compliant motion in unstructured environments.First,a controller is designed to modify the torque of each motor by focusing on the different motion states of the rolling gait.Second,an experimental platform is established for snake robots to verify the effectiveness of the controller.Finally,a series of rolling experiments are conducted using the torque-based rolling controller.In conclusion,the self-adaptive torque-based rolling controller enhances snake robot adaptability and mobility.
文摘With the advancement of deep learning in the automotive domain,more and more researchers are focusing on autonomous driving.Among these tasks,free space detection is particularly crucial.Currently,many model-based approaches have achieved autonomous driving on well-structured urban roads,but these efforts primarily focus on urban road environments.In contrast,there are fewer deep learningmethods specifically designed for off-road traversable area detection,and their effectiveness is not yet satisfactory.This is because detecting traversable areas in complex outdoor environments poses significant challenges,and current methods often rely on single-image inputs,which do not align with contemporary multimodal approaches.Therefore,in this study,we propose a CFH-Net model for off-road traversable area detection.This model employs a Transformer architecture to enhance its capability of capturing global information.For multimodal feature extraction and fusion,we integrate the CM-FRM module for feature extraction and introduce the novel FFX module for feature fusion,thereby improving the perception capability of autonomous vehicles on unstructured roads.To address upsampling,we propose a new convolution precorrection method to reduce model parameters and computational complexity while enhancing the model’s ability to capture complex features.Finally,we conducted experiments on the ORFD off-road dataset and achieved outstanding results.
基金This project is supported by National Hi-Tech Research and Development Program of China(863 Program, No.2001AA422360) Chinese Academy of Sciences Advanced Manufacturing Technology R&D Base Foundation, Chrna(No.F000112).
文摘A novel three-module robot has been introduced. It can change its configuration to adapt to the uneven terrain and to improve its tipover stability. This three-module tracked robot has three kinds of symmetry configuration. They are line type, triangle type, and row type. After the factors and the countermeasures of mobile robot＇s tipover problem are analyzed, stability pyramid and tipover stabil-ity index are proposed to globally determinate the mobile robot＇s static stability and dynamic stability. The shape shifting robot is tested by this technique under the combined disturbance of pitch, roll and yaw in simulation. The simulation result shows that this technique is effective for the analysis of mobile robot＇s tipover stability, especially for the reconfigurable or shape shifting modular robot. Experiments on three symmetry configurations are made under unstructured environments. The environment experiment shows the same result as that of the simulation that the triangle type configuration has the best stability. Both simulation and experiment provide a valid reference for the reconfigurable robot＇s potential application.
基金the Interdisciplinary Program of Shanghai Jiao Tong University(No.YG2019QNA25)。
文摘For safety reasons,in the automated dispensing medicines process,robots and humans cooperate to accomplish the task of drug sorting and distribution.In this dynamic unstructured environment,such as a humanrobot collaboration scenario,the safety of human,robot,and equipment in the environment is paramount.In this work,a practical and effective robot motion planning method is proposed for dynamic unstructured environments.To figure out the problems of blind zones of single depth sensor and dynamic obstacle avoidance,we first propose a method for establishing offline mapping and online fusion of multi-sensor depth images and 3D grids of the robot workspace,which is used to determine the occupation states of the 3D grids occluded by robots and obstacles and to conduct real-time estimation of the minimum distance between the robot and obstacles.Then,based on the reactive control method,the attractive and repulsive forces are calculated and transformed into robot joint velocities to avoid obstacles in real time.Finally,the robot’s dynamic obstacle avoidance ability is evaluated on an experimental platform with a UR5 robot and two KinectV2 RGB-D sensors,and the effectiveness of the proposed method is verified.
基金Sponsored by National"863"Program Project(1020021300704)
文摘Abstract： The supervised teleoperation control is presented for a mobile robot to implement the tasks by using fuzzy logic. The teleoperation control system includes joystick based user interaction mechanism, the high level instruction set and fuzzy logic behaviors integrated in a supervised autonomy teleoperation control system for indoor navigation. These behaviors include left wall following, right wall following, turn left, turn right, left obstacle avoidance, right obstacle avoidance and corridor following based on ultrasonic range finders data. The robot compares the instructive high level command from the operator and relays back a suggestive signal back to the operator in case of mismatch between environment and instructive command. This strategy relieves the operator＇s cognitive burden, handle unforeseen situations and uncertainties of environment autonomously. The effectiveness of the proposed method for navigation in an unstructured environment is verified by experiments conducted on a mobile robot equipped with only ultrasonic range finders for environment sensing.
文摘An algorithm is proposed for scheduling dependent tasks in time-varying heterogeneous multiprocessor systems, in which computational power and links between processors are allowed to change over time. Link contention is considered in the multiprocessor scheduling problem. A linear switching-state space-modeling paradigm is introduced to enable theoretical analysis from a system engineering perspective. Theoretical analysis of this model shows its robustness against changes in processing power and link failure. The proposed algorithm uses a fuzzy decision-making procedure to handle changes in the multiprocessor system. The efficiency of the proposed algorithm is illustrated by several random experiments and comparison against a recent benchmark approach. The results show up to 18% average improvement in makespan, especially for larger scale systems.
基金supported by the National Natural Science Foundation of China,China(32171909,52205254,32301704)the Guangdong Basic and Applied Basic Research Foundation,China(2023A1515011255,2020B1515120050,2024A1515010199)+1 种基金the Key Research Projects of Ordinary Universities in Guangdong Province,China(2024ZDZX1042,2024ZDZX3057)the Guangdong key R&D projects,China(202080404030001).
文摘In the complex orchard environment,precise picking point localization is crucial for the automation of fruit picking robots.However,existing methods are prone to positioning errors when dealing with complex scenarios such as short peduncles,partial occlusion,or complete misidentification,which can affect the actual work efficiency of the fruit picking robot.This study proposes an enhanced picking point localization method based on semantic reasoning for complex picking scenarios in vineyard.It innovatively designs three modules:the semantic reasoning module(SRM),the ROI threshold adjustment strategy(RTAS),and the picking point location optimization module(PPOM).The SRM is applied to handle the scenarios of grape peduncles being obstructed by obstacles,partial misidentification of peduncles,and complete misidentification of peduncles.The RTAS addresses the issue of low and short peduncles during the picking process.Finally,the PPOM optimizes the final position of the picking point,allowing the robotic arm to perform the picking operation with greater flexibility.Experimental results show that SegFormer achieves an mIoU(mean Intersection over Union)of 84.54%,with B_IoU and P_IoU reaching 73.90%and 75.63%,respectively.Additionally,the success rate of the improved fruit picking point localization algorithm reached 94.96%,surpassing the baseline algorithm by 8.12%.The algorithm's average processing time is 0.5428±0.0063 s,meeting the practical requirements for real-time picking.
