Autonomous navigation is a fundamental problem in robotics.Traditional methods generally build point cloud map or dense feature map in perceptual space;due to lack of cognition and memory formation mechanism,tradition...Autonomous navigation is a fundamental problem in robotics.Traditional methods generally build point cloud map or dense feature map in perceptual space;due to lack of cognition and memory formation mechanism,traditional methods exist poor robustness and low cognitive ability.As a new navigation technology that draws inspiration from mammal’s navigation,bionic navigation method can map perceptual information into cognitive space,and have strong autonomy and environment adaptability.To improve the robot’s autonomous navigation ability,this paper proposes a cognitive map-based hierarchical navigation method.First,the mammals’navigation-related grid cells and head direction cells are modeled to provide the robots with location cognition.And then a global path planning strategy based on cognitive map is proposed,which can anticipate one preferred global path to the target with high efficiency and short distance.Moreover,a hierarchical motion controlling method is proposed,with which the target navigation can be divided into several sub-target navigation,and the mobile robot can reach to these sub-targets with high confidence level.Finally,some experiments are implemented,the results show that the proposed path planning method can avoid passing through obstacles and obtain one preferred global path to the target with high efficiency,and the time cost does not increase extremely with the increase of experience nodes number.The motion controlling results show that the mobile robot can arrive at the target successfully only depending on its self-motion information,which is an effective attempt and reflects strong bionic properties.展开更多
A method to determine the direction angle for bionic navigation is proposed. In order to do it, observation models of polarized light were obtained through full-sky imaging polarimetry, and the symmetry line （ solar ...A method to determine the direction angle for bionic navigation is proposed. In order to do it, observation models of polarized light were obtained through full-sky imaging polarimetry, and the symmetry line （ solar meridian） was detected firstly; then the angle between solar meridian and the system moving direction was derived from simultaneous model, and the relative position of the sun was calculated by astronomical knowledge ; finally, the direction angle for bionic navigation was evaluated by utilizing sun azimuth to revise the angle between solar meridian and the system moving direction. This study improves previous conception with the changing solar meridian as a reference direction （0°） and provides a theoretic foundation for polarized light to be applied into navigation.展开更多
Some neurons in the brain of freely moving rodents show special firing pattern. The firing of head direction cells(HDCs) and grid cells(GCs) is related to the moving direction and distance, respectively. Thus, it is c...Some neurons in the brain of freely moving rodents show special firing pattern. The firing of head direction cells(HDCs) and grid cells(GCs) is related to the moving direction and distance, respectively. Thus, it is considered that these cells play an important role in the rodents' path integration. To provide a bionic approach for the vehicle to achieve path integration, we present a biologically inspired model of path integration based on the firing characteristics of HDCs and GCs. The detailed implementation process of this model is discussed. Besides, the proposed model is realized by simulation, and the path integration performance is analyzed under different conditions. Simulations validate that the proposed model is effective and stable.展开更多
基金funded by the National Natural Science Foundation of China-Liaoning Joint Fund(Grants:U20A20197)the National Natural Science Foundation of China(Grants:62173064)the Fundamental Research Funds for the Central Universities(Grants:N2326005).
文摘Autonomous navigation is a fundamental problem in robotics.Traditional methods generally build point cloud map or dense feature map in perceptual space;due to lack of cognition and memory formation mechanism,traditional methods exist poor robustness and low cognitive ability.As a new navigation technology that draws inspiration from mammal’s navigation,bionic navigation method can map perceptual information into cognitive space,and have strong autonomy and environment adaptability.To improve the robot’s autonomous navigation ability,this paper proposes a cognitive map-based hierarchical navigation method.First,the mammals’navigation-related grid cells and head direction cells are modeled to provide the robots with location cognition.And then a global path planning strategy based on cognitive map is proposed,which can anticipate one preferred global path to the target with high efficiency and short distance.Moreover,a hierarchical motion controlling method is proposed,with which the target navigation can be divided into several sub-target navigation,and the mobile robot can reach to these sub-targets with high confidence level.Finally,some experiments are implemented,the results show that the proposed path planning method can avoid passing through obstacles and obtain one preferred global path to the target with high efficiency,and the time cost does not increase extremely with the increase of experience nodes number.The motion controlling results show that the mobile robot can arrive at the target successfully only depending on its self-motion information,which is an effective attempt and reflects strong bionic properties.
基金Sponsored by Natural Science Foundation of Beijing(1093016)
文摘A method to determine the direction angle for bionic navigation is proposed. In order to do it, observation models of polarized light were obtained through full-sky imaging polarimetry, and the symmetry line （ solar meridian） was detected firstly; then the angle between solar meridian and the system moving direction was derived from simultaneous model, and the relative position of the sun was calculated by astronomical knowledge ; finally, the direction angle for bionic navigation was evaluated by utilizing sun azimuth to revise the angle between solar meridian and the system moving direction. This study improves previous conception with the changing solar meridian as a reference direction （0°） and provides a theoretic foundation for polarized light to be applied into navigation.
基金Project supported by the National Natural Science Foundation of China(No.61273048)
文摘Some neurons in the brain of freely moving rodents show special firing pattern. The firing of head direction cells(HDCs) and grid cells(GCs) is related to the moving direction and distance, respectively. Thus, it is considered that these cells play an important role in the rodents' path integration. To provide a bionic approach for the vehicle to achieve path integration, we present a biologically inspired model of path integration based on the firing characteristics of HDCs and GCs. The detailed implementation process of this model is discussed. Besides, the proposed model is realized by simulation, and the path integration performance is analyzed under different conditions. Simulations validate that the proposed model is effective and stable.
