Robotic systems are expected to play an increasingly important role in future space activities. The robotic on-orbital service, whose key is the capturing technology, becomes a research hot spot in recent years. This ...Robotic systems are expected to play an increasingly important role in future space activities. The robotic on-orbital service, whose key is the capturing technology, becomes a research hot spot in recent years. This paper studies the dynamics modeling and impedance control of a multi-arm free-flying space robotic system capturing a non-cooperative target. Firstly, a control-oriented dynamics model is essential in control algorithm design and code realization. Unlike a numerical algorithm, an analytical approach is suggested. Using a general and a quasi-coordinate Lagrangian formulation, the kinematics and dynamics equations are derived.Then, an impedance control algorithm is developed which allows coordinated control of the multiple manipulators to capture a target.Through enforcing a reference impedance, end-effectors behave like a mass-damper-spring system fixed in inertial space in reaction to any contact force between the capture hands and the target. Meanwhile, the position and the attitude of the base are maintained stably by using gas jet thrusters to work against the manipulators' reaction. Finally, a simulation by using a space robot with two manipulators and a free-floating non-cooperative target is illustrated to verify the effectiveness of the proposed method.展开更多
樱桃番茄串生长姿态多样、果实成熟度不一,采摘机器人进行“粒收”作业时,常面临果梗干涉末端执行器、成熟度判断错误等问题,导致采摘效率低下、难以有效实现分级采收。针对上述问题,该研究提出一种级联视觉检测流程,包括采收目标检测...樱桃番茄串生长姿态多样、果实成熟度不一,采摘机器人进行“粒收”作业时,常面临果梗干涉末端执行器、成熟度判断错误等问题,导致采摘效率低下、难以有效实现分级采收。针对上述问题,该研究提出一种级联视觉检测流程,包括采收目标检测、目标果实特性判别、果实与果梗位置关系判断3个关键环节。首先根据农艺要求按成熟度将番茄果实分为4个等级,引入YOLOv5目标检测模型对番茄串和番茄果实进行检测并输出成熟度等级,实现分期采收。然后对果实与果梗的相对位置进行判断,利用MobileNetv3网络模型对膨胀包围盒进行果实与果梗相对位置关系判断,实现末端执行器采摘位姿控制。日光温室实际测试结果表明,本文提出的级联检测系统平均推理用时22ms,在IOU(intersection over union)阈值为0.5的情况下,樱桃番茄串与果实的平均检测精度达到89.9%,满足采摘机器人的视觉检测精度和实时性要求,相比末端执行器以固定角度靠近待采目标的方法,本文方法采收效率提升28.7个百分点。研究结果可为各类果蔬采摘机器人研究提供参考。展开更多
A tomato harvesting robot was developed in this study,which consisted of a four-wheel independent steering system,a 5-DOF harvesting system,a navigation system,and a binocular stereo vision system.The four-wheel indep...A tomato harvesting robot was developed in this study,which consisted of a four-wheel independent steering system,a 5-DOF harvesting system,a navigation system,and a binocular stereo vision system.The four-wheel independent steering system was capable of providing a low-speed steering control of the robot based on Ackerman steering geometry.The proportional-integral-derivative(PID)algorithm was used in the laser navigation control system.The Otsu algorithm and the elliptic template method were used for the automatic recognition of ripe tomatoes,and obstacle avoidance strategies were proposed based on the C-space method.The maximum average absolute error between the set angle and the actual angle was about 0.14°,and the maximum standard deviation was about 0.04°.The laser navigation system was able to rapidly and accurately track the path,with the deviation being less than 8 cm.The load bearing capacity of the mechanical arm was about 1.5 kg.The success rate of the binocular vision system in the recognition of ripe tomatoes was 99.3%.When the distance was less than 600 mm,the positioning error was less than 10 mm.The time needed for recognition of ripe tomatoes and pitching was about 15 s per tomato,with a success rate of about 86%.This study provides some insights into the development and application of tomato harvesting robot used in the greenhouse.展开更多
针对大棚内除草环境复杂,且杂草种类繁多导致识别困难的特点,设计了一种机械式智能除草机器人。对试验田数据进行采集后,使用Yolov5模型进行150次迭代训练,最终训练出模型平均精度(map50)为82%,为了提高识别准确率,迭代次数增加到300次...针对大棚内除草环境复杂,且杂草种类繁多导致识别困难的特点,设计了一种机械式智能除草机器人。对试验田数据进行采集后,使用Yolov5模型进行150次迭代训练,最终训练出模型平均精度(map50)为82%,为了提高识别准确率,迭代次数增加到300次,最终模型平均精度(map50)为91%,机器人使用了Jetson Orin nano开发板为处理器,Intel D435深度摄像头进行数据采集,图像处理时间为1.2 ms,满足实时处理要求。采用机械式除草,减少了农药使用,该研究可为以后智能除草设备设计提供参考。展开更多
In developing and exploring extreme and harsh underwater environments,underwater robots can effectively replace humans to complete tasks.To meet the requirements of underwater flexible motion and comprehensive subsea ...In developing and exploring extreme and harsh underwater environments,underwater robots can effectively replace humans to complete tasks.To meet the requirements of underwater flexible motion and comprehensive subsea operation,a novel octopus-inspired robot with eight soft limbs was designed and developed.This robot possesses the capabilities of underwater bipedal walking,multi-arm swimming,and grasping objects.To closely interact with the underwater seabed environment and minimize disturbance,the robot employs a cable-driven flexible arm for its walking in underwater floor through a bipedal walking mode.The multi-arm swimming offers a means of three-dimensional spatial movement,allowing the robot to swiftly explore and navigate over large areas,thereby enhancing its flexibility.Furthermore,the robot’s walking arm enables it to grasp and transport objects underwater,thereby enhancing its practicality in underwater environments.A simplified motion models and gait generation strategies were proposed for two modes of robot locomotion:swimming and walking,inspired by the movement characteristics of octopus-inspired multi-arm swimming and bipedal walking.Through experimental verification,the robot’s average speed of underwater bipedal walking reaches 7.26 cm/s,while the horizontal movement speed for multi-arm swimming is 8.6 cm/s.展开更多
Acoustic positioning system has great potential to be applied in a greenhouse due to its centimeter-level accuracy,low cost,and ability of extensive greenhouse coverage.Spread Spectrum Sound-based local positioning sy...Acoustic positioning system has great potential to be applied in a greenhouse due to its centimeter-level accuracy,low cost,and ability of extensive greenhouse coverage.Spread Spectrum Sound-based local positioning system(SSSLPS)was proposed to be a navigation tool for multiple agricultural robots by the authors'research team.However,to increase the system capacity for positioning multiple robots in a greenhouse,the near-far problem caused by the interference between speakers needs to be overcome.The use of different access methods,Time Division Multiple Access(TDMA)or Frequency Division Multiple Access(FDMA),is essential in the SSSLPS system for solving the near-far problem.The static positioning in a greenhouse was first evaluated by setting different parameters to determine the optimal signal setting for a dynamic experiment.From that,the moving robot tests were added with a motion capture system and tested the performance of TDMA and FDMA.The results demonstrated that TDMA can be used in a stationary sound-based positioning system with 12.2 mm accuracy,but it has a time delay problem in dynamic positioning.A simulation was designed to mimic the position error increases with different moving speeds.Although FDMA has the sound damping problem in high-frequency regions creating a peak detection issue,it achieved a higher accuracy with an average position error of 62.1 mm compared to 180.3 mm of TDMA.This study shows that the TDMA method is suitable for static measurements,while the FDMA method is suitable for measuring dynamic objects and controlling mobile robots.展开更多
基金supported by the National Natural Science Foundation of China (61673009)。
文摘Robotic systems are expected to play an increasingly important role in future space activities. The robotic on-orbital service, whose key is the capturing technology, becomes a research hot spot in recent years. This paper studies the dynamics modeling and impedance control of a multi-arm free-flying space robotic system capturing a non-cooperative target. Firstly, a control-oriented dynamics model is essential in control algorithm design and code realization. Unlike a numerical algorithm, an analytical approach is suggested. Using a general and a quasi-coordinate Lagrangian formulation, the kinematics and dynamics equations are derived.Then, an impedance control algorithm is developed which allows coordinated control of the multiple manipulators to capture a target.Through enforcing a reference impedance, end-effectors behave like a mass-damper-spring system fixed in inertial space in reaction to any contact force between the capture hands and the target. Meanwhile, the position and the attitude of the base are maintained stably by using gas jet thrusters to work against the manipulators' reaction. Finally, a simulation by using a space robot with two manipulators and a free-floating non-cooperative target is illustrated to verify the effectiveness of the proposed method.
文摘樱桃番茄串生长姿态多样、果实成熟度不一,采摘机器人进行“粒收”作业时,常面临果梗干涉末端执行器、成熟度判断错误等问题,导致采摘效率低下、难以有效实现分级采收。针对上述问题,该研究提出一种级联视觉检测流程,包括采收目标检测、目标果实特性判别、果实与果梗位置关系判断3个关键环节。首先根据农艺要求按成熟度将番茄果实分为4个等级,引入YOLOv5目标检测模型对番茄串和番茄果实进行检测并输出成熟度等级,实现分期采收。然后对果实与果梗的相对位置进行判断,利用MobileNetv3网络模型对膨胀包围盒进行果实与果梗相对位置关系判断,实现末端执行器采摘位姿控制。日光温室实际测试结果表明,本文提出的级联检测系统平均推理用时22ms,在IOU(intersection over union)阈值为0.5的情况下,樱桃番茄串与果实的平均检测精度达到89.9%,满足采摘机器人的视觉检测精度和实时性要求,相比末端执行器以固定角度靠近待采目标的方法,本文方法采收效率提升28.7个百分点。研究结果可为各类果蔬采摘机器人研究提供参考。
基金supported by the National 863 planning project of China-digital design and intelligent control technology of agricultural facilities equipment(2013AA102406)the Beijing municipal science and technology project(Z161100004916118).
文摘A tomato harvesting robot was developed in this study,which consisted of a four-wheel independent steering system,a 5-DOF harvesting system,a navigation system,and a binocular stereo vision system.The four-wheel independent steering system was capable of providing a low-speed steering control of the robot based on Ackerman steering geometry.The proportional-integral-derivative(PID)algorithm was used in the laser navigation control system.The Otsu algorithm and the elliptic template method were used for the automatic recognition of ripe tomatoes,and obstacle avoidance strategies were proposed based on the C-space method.The maximum average absolute error between the set angle and the actual angle was about 0.14°,and the maximum standard deviation was about 0.04°.The laser navigation system was able to rapidly and accurately track the path,with the deviation being less than 8 cm.The load bearing capacity of the mechanical arm was about 1.5 kg.The success rate of the binocular vision system in the recognition of ripe tomatoes was 99.3%.When the distance was less than 600 mm,the positioning error was less than 10 mm.The time needed for recognition of ripe tomatoes and pitching was about 15 s per tomato,with a success rate of about 86%.This study provides some insights into the development and application of tomato harvesting robot used in the greenhouse.
文摘针对大棚内除草环境复杂,且杂草种类繁多导致识别困难的特点,设计了一种机械式智能除草机器人。对试验田数据进行采集后,使用Yolov5模型进行150次迭代训练,最终训练出模型平均精度(map50)为82%,为了提高识别准确率,迭代次数增加到300次,最终模型平均精度(map50)为91%,机器人使用了Jetson Orin nano开发板为处理器,Intel D435深度摄像头进行数据采集,图像处理时间为1.2 ms,满足实时处理要求。采用机械式除草,减少了农药使用,该研究可为以后智能除草设备设计提供参考。
基金provided by Hy Action Plan Project(Grant no.7172755A)the Key Projects of Science and Technology Plan of Zhejiang Province(Grant no.2019C04018)partially by the Ministry of Science and Higher Education of the Russian Federation as part of the World-class Research Center program:Advanced Digital Technologies(contract No.075-15-2022-312 dated 20.04.2022).
文摘In developing and exploring extreme and harsh underwater environments,underwater robots can effectively replace humans to complete tasks.To meet the requirements of underwater flexible motion and comprehensive subsea operation,a novel octopus-inspired robot with eight soft limbs was designed and developed.This robot possesses the capabilities of underwater bipedal walking,multi-arm swimming,and grasping objects.To closely interact with the underwater seabed environment and minimize disturbance,the robot employs a cable-driven flexible arm for its walking in underwater floor through a bipedal walking mode.The multi-arm swimming offers a means of three-dimensional spatial movement,allowing the robot to swiftly explore and navigate over large areas,thereby enhancing its flexibility.Furthermore,the robot’s walking arm enables it to grasp and transport objects underwater,thereby enhancing its practicality in underwater environments.A simplified motion models and gait generation strategies were proposed for two modes of robot locomotion:swimming and walking,inspired by the movement characteristics of octopus-inspired multi-arm swimming and bipedal walking.Through experimental verification,the robot’s average speed of underwater bipedal walking reaches 7.26 cm/s,while the horizontal movement speed for multi-arm swimming is 8.6 cm/s.
基金financially supported by the Japan Society for the Promotion of Science(JSPS)(Grant No.KAKENHI 18H05364)the JST SPRING(Grant No.JPMJSP2110)the Grant-in-Aid for JSPS Fellows(Project No.21F21397).
文摘Acoustic positioning system has great potential to be applied in a greenhouse due to its centimeter-level accuracy,low cost,and ability of extensive greenhouse coverage.Spread Spectrum Sound-based local positioning system(SSSLPS)was proposed to be a navigation tool for multiple agricultural robots by the authors'research team.However,to increase the system capacity for positioning multiple robots in a greenhouse,the near-far problem caused by the interference between speakers needs to be overcome.The use of different access methods,Time Division Multiple Access(TDMA)or Frequency Division Multiple Access(FDMA),is essential in the SSSLPS system for solving the near-far problem.The static positioning in a greenhouse was first evaluated by setting different parameters to determine the optimal signal setting for a dynamic experiment.From that,the moving robot tests were added with a motion capture system and tested the performance of TDMA and FDMA.The results demonstrated that TDMA can be used in a stationary sound-based positioning system with 12.2 mm accuracy,but it has a time delay problem in dynamic positioning.A simulation was designed to mimic the position error increases with different moving speeds.Although FDMA has the sound damping problem in high-frequency regions creating a peak detection issue,it achieved a higher accuracy with an average position error of 62.1 mm compared to 180.3 mm of TDMA.This study shows that the TDMA method is suitable for static measurements,while the FDMA method is suitable for measuring dynamic objects and controlling mobile robots.
