Sharif Digital Repository

Design and control of micro robots have been one of the interesting fields in robotics in recent years. One class of these micro robots is the legged robots. Various designs of legged robots have been proposed in the literature. All designs rely on friction for locomotion. In this paper dynamic model of a planar two-legged micro robot is presented using Luger friction model, and an adaptive neural controller used to control the robot to improve robustness and velocity of the robot. As mentioned earlier, friction plays an important role in locomotion of the legged robots. However, especially in legged micro robots, it is difficult to model the frictional force correctly since environmental... 

According to the fact that humans and animals show marvelous abilities in walking on irregular terrain, there is a strong need for adaptive algorithms in walking of biped robots to behave like them. Since the stance leg can easily rise from the ground and it can easily rotate about the toe or the heel, the problem of controlling the biped robots is difficult. In this paper, according to the adaptive locomotion patterns of animals, coordination and control of body links have been done with Central Pattern Generator (CPG) in spinal cord and feedback network from musculoskeletal system. A one layer feedforward neural network that its inputs are the scaled joint variables and the touch sensors... 

Despite development of accurate musculoskeletal models for human lumbar spine, the methods for prediction of muscle activity patterns in movements lack proper association with corresponding sensorimotor integrations. This paper uses the directional information of the Jacobian of the musculoskeletal system to orchestrate adaptive critic-based fuzzy neural controller modules for controlling a complex nonlinear redundant musculoskeletal system. The proposed controller is used to control a 3D 3-degree of freedom (DOF) musculoskeletal model of trunk, actuated by 18 muscles. The controller is capable of learning to control from sensory information, without relying on pre-assumed model parameters.... 

The complexity associated with musculoskeletal modeling, simulation, and neural control of the human spine is a challenging problem in the field of biomechanics. This paper presents a novel method for simulation of a 3D trunk model under control of 48 muscle actuators. Central pattern generators (CPG) and artificial neural network (ANN) are used simultaneously to generate muscles activation patterns. The parameters of the ANN are updated based on a novel learning method used to address the kinetic redundancy due to presence of 48 muscles driving the trunk. We demonstrated the feasibility of the proposed method with numerical simulation of experiments involving rhythmic motion between upright... 

The canonical problems in control of the biped robots arise from underactuation, impulsive nature of the impact with the environment and existence of the many degrees of freedom in their mechanism. Since biped walkers have fewer actuators than degrees of freedom, they are underactuated mechanical systems. In this paper according to the humans and animals locomotion algorithms, the stability of an underactuated biped walker with point feet is done by central pattern generator and feedback networks. For tuning the parameters of the CPG network, the control problem is defined as an optimization problem. This optimization problem is solved by using of Genetic algorithm. Also a new feedback... 

According to the fact that humans and animals show marvelous abilities in walking on irregular terrain, there is a strong need for adaptive algorithms in walking of biped robots to behave like them. Since the stance leg can easily rise from the ground and it can easily rotate about the toe or the heel, the problem of controlling the biped robots is difficult. In this paper, according to the adaptive locomotion patterns of animals, coordination and control of body links have been done with Central Pattern Generator (CPG) in spinal cord and feedback network from musculoskeletal system. A one layer feedforward neural network that its inputs are the scaled joint variables and the touch sensors... 

According to the fact that humans and animals show marvelous capacities in walking on irregular terrain, there is a strong need for adaptive algorithms in walking of biped robots to behave like them. Since the stance leg can easily rise from the ground, the problem of controlling the biped robots is difficult. In other words, the biped walkers have fewer actuators than the degrees of freedom. So they are underactuated mechanical systems. In this paper according to the humans and animals locomotion algorithms, the stability of an underactuated biped walker having point feet is investigated by central pattern generators. For tuning the parameters of the CPG, an effective energy based...