Rolling Biped Polynomial Motion Planning

This work discloses a kinematic control model to describe the geometry of motion of a two-wheeled biped’s limbs. Limb structure is based on a four-bar linkage useful to alleviate damping motion during self-balance. The robot self-balancing kinematics geometry combines with user-customized polynomial vector fields. The vector fields generate safe reference trajectories. Further, the robot is forced to track the reference path by a model-based time-variant recursive controller. The proposed formulation showed effectiveness and reliable performance through numerical simulations.

Control of Thruster-Assisted, Bipedal Legged Locomotion of the Harpy Robot

Fast constraint satisfaction, frontal dynamics stabilization, and avoiding fallovers in dynamic, bipedal walkers can be pretty challenging. The challenges include underactuation, vulnerability to external perturbations, and high computational complexity that arise when accounting for the system full-dynamics and environmental interactions. In this work, we study the potential roles of thrusters in addressing some of these locomotion challenges in bipedal robotics. We will introduce a thruster-assisted bipedal robot called Harpy. We will capitalize on Harpy’s unique design to propose an optimization-free approach to satisfy gait feasibility conditions. In this thruster-assisted legged locomotion, the reference trajectories can be manipulated to fulfill constraints brought on by ground contact and those prescribed for states and inputs. Unintended changes to the trajectories, especially those optimized to produce periodic orbits, can adversely affect gait stability and hybrid invariance. We will show our approach can still guarantee stability and hybrid invariance of the gaits by employing the thrusters in Harpy. We will also show that the thrusters can be leveraged to robustify the gaits by dodging fallovers or jumping over large obstacles.

A modified direct inverse Prandtl–Ishlinskii model based on two sets of operators for the piezoelectric actuator hysteresis compensation

Piezoelectric actuator (PEA) is widely applied in the field of micro/nano high precision positioning. However PEA has the phenomenon of hysteresis non-linearity between input voltage and output displacement, due to the natural property of piezoelectric materials. The PEA hysteresis can be compensated by hysteresis models, which makes the input voltage and output displacement more linearity. The research work on compensation of PEA hysteresis by using various hysteresis models has been being a hot topic. This paper presents a modified direct inverse rate-independent Prandtl–Ishlinskii (PI) (MDIPI) model for compensating the hysteresis of PEA. The proposed MDIPI model has two different sets of operators compared with classical PI (CPI) model having one set of operators. For the two sets operators in MDIPI model one is rate operators and the other is modified classical operators. By combining the two sets operators, the MDIPI model has the properties of the adaption and accuracy in hysteresis compensation. The MDIPI model can be used as feedforward controller to compensate different reference trajectories. Parameters of MDIPI model are calculated by matlab optimization tool box. The experiments of compensating the complex displacement trajectory and sinusoidal trajectory are validated on a platform of commercial PEA. The MDIPI model has achieved more accurate results than the Krasnosel’skii–Pokrovkii (KP), Preisach and CPI models. It is effective in improving the accuracy of PEA hysteresis compensation.

Output feedback averaged sub-gradient integral sliding mode control to regulate the tridimensional autonomous motion of autonomous submersible vehicles

This study presents the development of an output feedback control for regulating the movement of an autonomous submersible vehicles in the tridimensional space. The controller formulation applies the Averaged Sub-Gradient Integral Sliding Mode which is fed with the estimation of the translational velocity states by a distributed super-twisting algorithm. The structure of the autonomous submersible vehicles dynamics permits the implementation of the ASG algorithm using the estimates of translation velocity. The proposed scheme solves a non-linear extremum seeking problem that aims to minimize a non-strictly convex function that depends on the tracking error defined by the difference of some suitable reference trajectories and the coordinates of the submarine center of mass. The desired reference trajectories were designed to force the autonomous submersible vehicles three-dimensional motion to a continuous circuit in an oscillating shape over the horizontal plane combined with a submersion on the z-axis. The comparison between the proposed controller, the ASG with complete knowledge of the states and the state feedback controller is presented. This comparison confirms the output feedback ASG controller forced the autonomous submersible vehicles to the desired trajectory with a notable difference in the magnitude of the control given the estimation of the states. These outcomes justify the potential contributions of the suggested ASG integrated with the super-twisting algorithm to obtain the local minimization of the evaluated functional depending on the tracking error. The results justify the potential contributions of the suggested ASG with the super-twisting algorithm to regulate the position of the autonomous submersible vehicles to the desired trajectory.

Impact of Chinese and European Airspace Constraints on Trajectory Optimization

Air traffic trajectory optimization is a complex, multidimensional and non-linear optimization problem and requires a firm focus on the essential criteria. The criteria cover operational, economical, environmental, political, and social factors and differ from continent to continent. Since air traffic is a transcontinental transport system, the criteria may also change during a single flight. Historic flight track data allow observation and assess real flights, to extract essential criteria and to derive optimization strategies to increase air traffic efficiency. Real flight track data from the Chinese and European air traffic show significant differences in the routing structure in both regions. For that reason, reference trajectories of historic ADS-B 24-h air traffic data in China and Europe have been extracted and analyzed regarding horizontal flight efficiency and the most restrictive criteria of trajectory optimization. We found that prohibited areas might be the most powerful reason to describe deviations from the great circle distance in the Chinese air traffic system. Atmospheric conditions, network requirements, aircraft types and flight planning procedures are similar in China and Europe and only have a minor impact on flight efficiency during the cruise phase. In a multi-criteria trajectory optimization of the extracted reference trajectories considering the weather, operational constraints and prohibited areas, we found that flown ground distances could be reduced by 255 km in the Chinese airspace and 2.3 km in the European airspace. The resultant reference trajectories can be used for further analysis to increase the efficiency of continental air traffic flows.

A modular framework to generate robust biped locomotion: from planning to control

Biped robots are inherently unstable because of their complex kinematics as well as dynamics. Despite many research efforts in developing biped locomotion, the performance of biped locomotion is still far from the expectations. This paper proposes a model-based framework to generate stable biped locomotion. The core of this framework is an abstract dynamics model which is composed of three masses to consider the dynamics of stance leg, torso, and swing leg for minimizing the tracking problems. According to this dynamics model, we propose a modular walking reference trajectories planner which takes into account obstacles to plan all the references. Moreover, this dynamics model is used to formulate the controller as a Model Predictive Control (MPC) scheme which can consider some constraints in the states of the system, inputs, outputs, and also mixed input-output. The performance and the robustness of the proposed framework are validated by performing several numerical simulations using MATLAB. Moreover, the framework is deployed on a simulated torque-controlled humanoid to verify its performance and robustness. The simulation results show that the proposed framework is capable of generating biped locomotion robustly.

Landing Trajectory Design for UAV Considering Control Restrictions and Landing Speed

The article presents a method for designing the trajectory of the UAV in space, taking into account the restriction on control. The chosen optimal controls are namely normal overload with restrictions, tangential overload with restrictions, and lateral overload. The Pontryagin maximum principle allows the transition of the optimal control problem to a boundary value problem. The parameter continuation method is applied to solve the boundary problem. The article results reveal reference trajectories in different cases of UAV landing. This result allows the design of reference trajectories for the UAV to attain the highest landing efficiency.

Decentralized Control of Nanosatellite Tetrahedral Formation Flying Using Aerodynamic Forces

A decentralized control algorithm for the construction of a tetrahedral configuration using differential lift and drag forces is proposed in this paper. Four 3U CubeSats launched in LEO are considered. Satellite attitude-controlled motion relative to the incoming airflow provides the required differential forces in order to change the relative translational motion. The developed control algorithm allows one to track the relative reference trajectories for the satellites at the vertices of the tetrahedron of the required shape and size. The influence of the initial launch conditions on the controlled tetrahedral motion is studied in this paper.

Nonlinear Model Predictive Horizon for Optimal Trajectory Generation

This paper presents a trajectory generation method for a nonlinear system under closed-loop control (here a quadrotor drone) motivated by the Nonlinear Model Predictive Control (NMPC) method. Unlike NMPC, the proposed method employs a closed-loop system dynamics model within the optimization problem to efficiently generate reference trajectories in real time. We call this approach the Nonlinear Model Predictive Horizon (NMPH). The closed-loop model used within NMPH employs a feedback linearization control law design to decrease the nonconvexity of the optimization problem and thus achieve faster convergence. For robust trajectory planning in a dynamically changing environment, static and dynamic obstacle constraints are supported within the NMPH algorithm. Our algorithm is applied to a quadrotor system to generate optimal reference trajectories in 3D, and several simulation scenarios are provided to validate the features and evaluate the performance of the proposed methodology.

Practical Tracking Control of a Class of Uncertain Surface Vessels Under Weak Assumptions on Uncertainties and Reference Trajectories

This paper is devoted to the tracking control of a class of uncertain surface vessels. The main contributions focus on the considerable relaxation of the severe restrictions on system uncertainties and reference trajectory in the related literature. Specifically, all the system parameters are unknown and the disturbance is not necessarily to be differentiable in the paper, but either unknown parameters or disturbance is considered but the other one is excluded in the related literature, or both of them are considered but the disturbance must be continuously differentiable. Moreover, the reference trajectories in the related literature must be at least twice continuously differentiable and themselves as well as their time derivatives must be known for feedback, which are generalized to a more broad class ones that are unknown and only one time continuously differentiable in the paper. To solve the control problem, a novel practical tracking control scheme is presented by using backstepping scheme and adaptive technique, and in turn to derive an adaptive state-feedback controller which guarantees that all the states of the resulting closed-loop system are bounded while the tracking error arrives at and then stay within an arbitrary neighborhood of the origin. Finally, simulation is provided to validate the effectiveness of the proposed theoretical results.