Journal of Intelligent and Robotic Systems

This paper considers the question of obtaining a nonlinear trajectory tracking control law for a comprehensive design of a Gun Launched Micro Aerial Vehicle (GLMAV) despite unknown aerodynamic efforts. To this purpose, a nonlinear mathematical model of the GLMAV is firstly presented for hover and near hover flight conditions. Then, an approximate backstepping control law is derived, allowing the trajectory tracking and the stabilization of the vehicle’s position and orientation while on-line estimating the unknown aerodynamics efforts. The main idea of the control law is to separate the controller into a position controller in cascade with an orientation controller. The control design will be extended such that the interconnection term between the cascaded sub-systems is minimised. Finally, numerical simulations are used to demonstrate the control law’s good performance.

Flexible robots have exhibited impressive features in working in congested environments due to their compliance behavior and morphological structure. However, designing motion planning techniques and robust control strategies that actively control their deformations are challenging in many applications. Thus, this article presents the learning by Demonstration (LbD) approach for planning the spatial point-to-point motions of a multi-section continuum robot. Via teleoperation, the human demonstrations are captured by moving the flexible interface with similar kinematics of the active robot in front of the Motion Capture System (MCS). Meanwhile, a Nonlinear Model Predictive Control (NMPC) scheme is proposed based on the robot’s kinematic model to follow the reference trajectories while respecting the constraints imposed by the cable lengths and control actions. The simulation results prove the efficiency of the LbD approach in reproducing and generalizing the spatial motions of the robot’s tip and avoiding obstacles and external disturbances. On the other hand, the numerical simulations show the performance of NMPC scheme in terms of trajectory tracking and avoiding static and dynamic obstacles. Additionally, its robustness is analyzed by comparing it to the Pseudo-Inverse Jacobian Kinematic Control (PIJKC) while considering the constraints of cable lengths. Finally, the stability of NMPC is evaluated against input perturbations using the Monte Carlo simulations.

This paper proposes the novel adaptive neural network (ADNN) compliant force/position control algorithm applied to a highly nonlinear serial pneumatic artificial muscle (PAM) robot as to improve its compliant force/position output performance. Based on the new adaptive neural ADNN model which is dynamically identified to adapt well all nonlinear features of the 2-axes serial PAM robot, a new hybrid adaptive neural ADNN-PID controller was initiatively implemented for compliant force/position controlling the serial PAM robot system used as an elbow and wrist rehabilitation robot which is subjected to not only the internal coupled-effects interactions but also the external end-effecter contact force variations (from 10[N] up to critical value 30[N]). The experiment results have proved the feasibility of the new control approach compared with the optimal PID control approach. The novel proposed hybrid adaptive neural ADNN-PID compliant force/position controller successfully guides the upper limb of subject to follow the linear and circular trajectories under different variable end-effecter contact force levels.

Path planning and formation control are two of the most significant concepts which can be considered in multi-vehicle systems and particularly in autonomous underwater vehicles (AUVs). The cooperative implementation of complicated commands would lead to desirable results and increase the probability of success in the missions. Due to the nonlinear dynamics and environmental conditions, the cooperative control of AUVs is a challenging topic. The developments in AUV applications demonstrate the significance of research and development in path planning and formation control. Unlike ground or aerial autonomous vehicles, this field of study has not attracted considerable attention and further exploration is required as a result. The present paper reviews the different structures of formation control in AUVs and discusses their advantages and disadvantages. Besides formation control, the cooperative path planning of AUVs along with the limitations specific to the cooperative structure is taken into consideration in the present study. Moreover, avoiding any obstacle collision and preventing any encounter between group members are considered as critical issues in the formation control and cooperative path planning. Some areas are still open to investigation as implied by the technological suggestions, which will facilitate future research. At the end of the article, a simulated sample is given of the triangular formation path planning for AUVs.