s. ali a. moosavian

Continuum robotic arms that are inspired from nature, have many advantages compared to traditional robots, which motivate researchers in this field. Dynamic modeling and controlling these robots are challenging subjects due to complicated nonlinearities and considerable uncertainties existing in these structures. In this paper, first a dynamic three-dimensional model of the continuum robotic arm is developed as a black-box model through system identification method. The validity of the obtained model is confirmed by the experimental data. Then, by using the obtained model, a hybrid PID-fuzzy controller, which is considered as a model-free controller and does not require the exact model of the system is employed for controlling the position of the end-effector. Finally, obtained results and the performance of the controller in reaching to different positions of the workspace, either trained or not, is discussed.

Utilizing orthosis and exoskeletons has drawn a lot of attention in many applications including medical industries. These devices are used in the area of physical therapy to facilitate the patient’s exercises and as an assisting device to help the elderly carry out their daily activities. In this paper, the RoboWalk body-weight support assist device is introduced and its performance is analyzed by studying its influence on a human model. For this purpose, the forward kinematics of the human model and the inverse kinematics of RoboWalk are introduced in the first step. The dynamics of the human and a comprehensive model for RoboWalk are then obtained using the Newton-Euler method without considering the contact forces. These forces are then included in the model using the jacobian of contact points. The obtained models are then augmented to estimate the RoboWalk joint forces and torques, and those of the human model. The Recursive Newton Euler Algorithm and ADAMS software are used to verify the modeling obtained from the non-recursive Newton-Euler algorithm. The recursive algorithm is suitable for implementation purposes due to its low computational cost. After ensuring the accuracy of the obtained models, a control strategy is designed and implemented on RoboWalk. The performance of RoboWalk is then investigated by defining some criteria, e.g. floor reaction force and human model joint torques, before and after using RoboWalk.

Quadruped robots have unique capabilities for motion over uneven natural environments. This article presents a stable gait for a quadruped robot in such motions and discusses the inverse-dynamics control scheme to follow the planned gait. First, an explicit dynamics model will be developed using a novel constraint elimination method for an 18-DOF quadruped robot. Thereafter, an inverse-dynamics control will be introduced using this model. Next, a dynamically stable condition under sufficient friction assumption for the motion of the robot on uneven terrains will be obtained. Satisfaction of this condition assures that the robot does not tip over all the support polygon edges. Based on this stability condition, a constrained optimization problem is defined to compute a stable and smooth center of gravity (COG) path. The main feature of the COG path is that the height of the robot can be adjusted to follow the terrain. Then, a path generation algorithm for tip of the swing legs will be developed. This smooth path is planned so that any collision with the environment is avoided. Finally, the effectiveness of the proposed method will be verified.

This paper proposes a gait planning approach to reduce the required friction for a biped robot walking on various surfaces. To this end, a humanoid robot with 18 DOF is considered to develop a dynamics model for studying various 3D manoeuvres. Then, feasible trajectories are developed to alleviate the fluctuations on the upper body to resemble human-like walking. In order to generate feasible walking patterns, not only horizontal interaction moments for the computation of ZMP, but also horizontal forces and vertical moment constraints between the feet and the ground surface are taken into account. Since the pelvis trajectory does drastically affect the walking pattern, the focus will be on generating a smooth motion for the pelvis. This smooth motion is generated based on a desired motion for the robot’s Centre of Mass (COM), which is mapped to the joint space using inverse kinematics. In fact, the proposed approach involves computing a moving ZMP based on a predefined desired COM trajectory to reduce the required friction for stable walking. The suggested gait planning approach (Low Friction Demanding Moving-ZMP, LFDM) is compared to various existing approaches considering slippage conditions. The obtained results reveal the effectiveness of the proposed method for various walking speeds which will be discussed.

In this paper, the vision based formation control of a leader-follower aerial robotic system is discussed while communication failure between the robots is considered. Based on vision sensors and image processing computations, without any need to further communications, the follower robot obtains the line of sight angle and the corresponding distance from the leader. These information are used to calculate the leader speed and its path angle. Using model predictive control method, it is shown that even in the presence of communication failure between the robots, the flight formation can be controlled while the follower moves along the desired relative angle and keeps the corresponding distance. To this end, the control inputs are obtained in terms of normal and tangential acceleration of the follower. Simulation results show a good performance of the proposed model predictive controller in both ordinary, and communication failure conditions.