Bio-inspired kinematical control of redundant robotic manipulators

Purpose – This paper aims to propose an innovative kinematic control algorithm for redundant robotic manipulators. The algorithm takes advantage of a bio-inspired approach. Design/methodology/approach – A simplified two-degree-of-freedom model is presented to handle kinematic redundancy in the x-y plane; an extension to three-dimensional tracking tasks is presented as well. A set of sample trajectories was used to evaluate the performances of the proposed algorithm. Findings – The results from the simulations confirm the continuity and accuracy of generated joint profiles for given end-effector trajectories as well as algorithm robustness, singularity and self-collision avoidance. Originality/value – This paper shows how to control a redundant robotic arm by applying human upper arm-inspired concept of inter-joint dependency

What Strategy Central Nervous System Uses to Perform a Movement Balanced? Biomechatronical Simulation of Human Lifting

How does the central nervous system control the body posture during various tasks despite a redundancy? It's a well-known question existed in such fields of study as biomechanics and bioengineering. Some techniques based on muscle and torques synergies are presented to study the function which Central Nervous System uses to addresses the kinetic redundancy in musculoskeletal system. The human body with its whole numerous joints considered as a hyper redundant structure which caused to be seemed that it is impossible for CNS to control and signal such system. To solve the kinematic redundancy in previous studies it is hypothesize that CNS functions as an optimizer, such of that are the task-based algorithms which search to find optimal solution for each specific task. In this research a new objective function based on ankle torques during movement is implemented to guarantee the stability of motion. A 2D 5DOF biomechatronical model of human body is subjected to lifting task simulation. The simulation process implements inverse dynamics as major constraint to consider the dynamics of motion for predicted postures. In the previous optimization-based techniques which are used to simulate the human movements, the motion stability was guaranteed by a nonlinear inequality constraint which restricts the total moment arm of the links to an upper and lower boundary. In this method, there is no need to use this constraint. The results show that the simulated postures are normal and the predicted motion is performed completely balanced

What strategy central nervous system uses to perform a movement balanced? Biomechatronical simulation of human lifting

How does the central nervous system control the body posture during various tasks despite a redundancy? It's a well-known question existed in such fields of study as biomechanics and bioengineering. Some techniques based on muscle and torques synergies are presented to study the function which Central Nervous System uses to addresses the kinetic redundancy in musculoskeletal system. The human body with its whole numerous joints considered as a hyper redundant structure which caused to be seemed that it is impossible for CNS to control and signal such system. To solve the kinematic redundancy in previous studies it is hypothesize that CNS functions as an optimizer, such of that are the task-based algorithms which search to find optimal solution for each specific task. In this research a new objective function based on ankle torques during movement is implemented to guarantee the stability of motion. A 2D 5DOF biomechatronical model of human body is subjected to lifting task simulation. The simulation process implements inverse dynamics as major constraint to consider the dynamics of motion for predicted postures. In the previous optimization-based techniques which are used to simulate the human movements, the motion stability was guaranteed by a nonlinear inequality constraint which restricts the total moment arm of the links to an upper and lower boundary. In this method, there is no need to use this constraint. The results show that the simulated postures are normal and the predicted motion is performed completely balanced

Modelling and simulation of human-like movements for humanoid robots

The humanoid robots are bio-inspired models of human body. The mechanical structure of humanoid robots consists of several joints and segments. Numerous degrees of freedom are caused the redundancy problem. There is an unanswered question concerning with strategies which central nervous system implements to predict the human posture and gesture during different movements. A 7 degree of freedom model is used for modelling humanoid robot and an optimization-based method is planned to simulation of human motion. The joints angles and torques are subjected as optimization variables. The joints range of motion and limits of actuator torques are used as optimization constraints. The weight lifting is the motion which is subjected to simulation. Finally the results presented for two velocity lifting. The result shows the body posture varies naturally and the weight maintain at the end position at final time correctly

Realistic dynamic posture prediction of humanoid robot : Manual lifting task simulation

A well known question mooted in biomechanics is how the central nerves system manages the body posture during various tasks. A 5DOF biomechatronical model of human body subjected to simulate the manual lifting task of humanoid robot. Simulation process is based on optimization approach named predictive dynamics using inverse dynamics. An objective function in term of ankle torques during lifting time, subjected to be minimized. It assumed that CNS considered this function to perform lifting motion balanced. In the other optimization-based simulations, balancing motion was guaranteed by a nonlinear inequality constraint which restricts the total moment arm of the links to an upper and lower boundary. In this method there is no need to use this constraint. Result shows that the motion is performed balanced. According to the comparison the results with the experimental data, the body posture of humanoid robots, predicted as similar as actual human posture

Posture prediction of humanoid robot : Modeling and simulation of manual lifting

How the central nervous system manage the body posture during various tasks despite redundancy problem? It's a well known question mooted in area of research such as biomechanics and medicine. Some techniques based on muscle and torques synergies presented to express CNS addressing the kinetic redundancy in musculoskeletal system. A 5DOF biomechatronical model of human body subjected to simulate the manual lifting task of humanoid robot. Simulation process is based on optimization approach named predictive dynamics. It uses inverse dynamics to consider the dynamics of motion in simulation process. An objective function in term of ankle torques during lifting time, subjected to be minimized. It assumed that CNS considered this function to perform lifting motion balanced. In the other optimization-based simulations, balancing motion was guaranteed by a nonlinear inequality constraint which restricts the total moment arm of the links to an upper and lower boundary. In this method there is no need to use this constraint. Result shows that the motion is performed balanced. According to the comparison the results with the experimental data, the body posture of humanoid robots, predicted as similar as actual human posture

Dynamic walking with a soft limb robot

We present a novel soft limb quadruped robot “FASTT,” with a simple and cheap design of its legs for dynamic locomotion aimed to expand the applications of soft robotics in mobile robots. The pneumatically actuated soft legs are self-stabilizing, adaptive to ground, and have variable stiffness, all of which are essential properties of locomotion that are also found in biological systems. We tested the soft legs for the pace, trot, and gallop gait and found them to move with a forward velocity for each gait with robustness. The legs were able to produce a flight and stance phase as a result of the bodyenvironment interaction and also support the weight of the body while two legs were in flight phase and two in stance phase. The soft robot also exhibited two different postures i.e. sprawl and semi-erect which can also be found in some biological species as the crocodile. Moreover, the robot is safe to interact with. The results highlight the effectiveness of the soft limbs to produce dynamic locomotion which provides potential for application in uncertain environments

Dynamic Walking with a Soft Limb Robot

We present a novel soft limb quadruped robot "FASTT," with a simple and cheap design of its legs for dynamic locomotion aimed to expand the applications of soft robotics in mobile robots. The pneumatically actuated soft legs are self-stabilizing, adaptive to ground, and have variable stiffness, all of which are essential properties of locomotion that are also found in biological systems. We tested the soft legs for the pace, trot, and gallop gait and found them to move with a forward velocity for each gait with robustness. The legs were able to produce a flight and stance phase as a result of the body-environment interaction and also support the weight of the body while two legs were in flight phase and two in stance phase. The soft robot also exhibited two different postures i.e. sprawl and semi-erect which can also be found in some biological species as the crocodile. Moreover, the robot is safe to interact with. The results highlight the effectiveness of the soft limbs to produce dynamic locomotion which provides potential for application in uncertain environments