Climbing robots are being developed for various applications.The confined space requires a compact locomotion system with vertical and overhead climbing ability.To achieve surface transition,Steering geometry Interact...Climbing robots are being developed for various applications.The confined space requires a compact locomotion system with vertical and overhead climbing ability.To achieve surface transition,Steering geometry Interaction system and static force are used.WSNs ubiquitous infrastructure and excellent coverage,they can be used for providing location information for various location-based services,especially in indoor environments.This structure is designed for a magnetic wall-climbing robot to gradually decrease the magnetic force when it is transiting between perpendicular magnetic surfaces.This paper describes the design process of a magnetic wall climbing robot,which adopts SgI and has the potential to carry materials in a confined space with an energy efficient system model.To resolve the problem of target tracking,it is essential to deploy a system model.Over the last two decades,several researchers have recommended many remote user authentication schemes.Researchers are continuously trying to enhance the security in material handling automation system by introducing several features into their work.A working prototype has been built based on the optimized dimension.展开更多
Learning and self-adaptation ability is highly required to be integrated in path planning algorithm for underwater robot during navigation through an unspecified underwater environment. High frequency oscillations dur...Learning and self-adaptation ability is highly required to be integrated in path planning algorithm for underwater robot during navigation through an unspecified underwater environment. High frequency oscillations during underwater motion are responsible for nonlinearities in dynamic behavior of underwater robot as well as uncertainties in hydrodynamic coefficients. Reactive behaviors of underwater robot are designed considering the position and orientation of both target and nearest obstacle from robot s current position. Human like reasoning power and approximation based learning skill of neural based adaptive fuzzy inference system（ANFIS）has been found to be effective for underwater multivariable motion control. More than one ANFIS models are used here for achieving goal and obstacle avoidance while avoiding local minima situation in both horizontal and vertical plane of three dimensional workspace.An error gradient approach based on input-output training patterns for learning purpose has been promoted to spawn trajectory of underwater robot optimizing path length as well as time taken. The simulation and experimental results endorse sturdiness and viability of the proposed method in comparison with other navigational methodologies to negotiate with hectic conditions during motion of underwater mobile robot.展开更多
文摘Climbing robots are being developed for various applications.The confined space requires a compact locomotion system with vertical and overhead climbing ability.To achieve surface transition,Steering geometry Interaction system and static force are used.WSNs ubiquitous infrastructure and excellent coverage,they can be used for providing location information for various location-based services,especially in indoor environments.This structure is designed for a magnetic wall-climbing robot to gradually decrease the magnetic force when it is transiting between perpendicular magnetic surfaces.This paper describes the design process of a magnetic wall climbing robot,which adopts SgI and has the potential to carry materials in a confined space with an energy efficient system model.To resolve the problem of target tracking,it is essential to deploy a system model.Over the last two decades,several researchers have recommended many remote user authentication schemes.Researchers are continuously trying to enhance the security in material handling automation system by introducing several features into their work.A working prototype has been built based on the optimized dimension.
文摘Learning and self-adaptation ability is highly required to be integrated in path planning algorithm for underwater robot during navigation through an unspecified underwater environment. High frequency oscillations during underwater motion are responsible for nonlinearities in dynamic behavior of underwater robot as well as uncertainties in hydrodynamic coefficients. Reactive behaviors of underwater robot are designed considering the position and orientation of both target and nearest obstacle from robot s current position. Human like reasoning power and approximation based learning skill of neural based adaptive fuzzy inference system（ANFIS）has been found to be effective for underwater multivariable motion control. More than one ANFIS models are used here for achieving goal and obstacle avoidance while avoiding local minima situation in both horizontal and vertical plane of three dimensional workspace.An error gradient approach based on input-output training patterns for learning purpose has been promoted to spawn trajectory of underwater robot optimizing path length as well as time taken. The simulation and experimental results endorse sturdiness and viability of the proposed method in comparison with other navigational methodologies to negotiate with hectic conditions during motion of underwater mobile robot.
