Seam-tracking based on dynamic trajectory planning for a mobile welding robot

A new seam-tracking method based on dynamic trajectory planning for a mobile welding robot is proposed in order to improve the response lag of the mobile robot and the high frequency oscillation in seam-tracking.By using a front-placed laser-based vision sensor to dynamically extract the location of the weld seam in front of torch,the trend and direction of the weld line is roughly obtained.The robot system autonomously and dynamically performs trajectory planning based on the isometric approximation model.Arc sensor technology is applied to detect the offset during welding process in real time.The dynamic compensation of the weld path is done in combination with the control of the mobile robot and the executive body installed on it.Simulated and experimental results demonstrate that the method effectively increases the stability of welding speed and smoothness of the weld track,and hence the weld formation in curves and corners is improved.

Dynamic Trajectory Planning of Autonomous Lane Change at Medium and Low Speeds Based on Elastic Soft Constraint of the Safety Domain

Most current research on the trajectory planning of the autonomous lane change focuses on high-speed scenarios and assumes that the states of the surrounding vehicles keep stable during the lane change.The methods based on geometric-curve are mostly used for trajectory planning.In this paper,considering the inevitable development of the autonomous driving,the surrounding vehicles are assumed to be driven by human drivers,while the ego vehicles are able to autonomously change lanes.Representative local lane-change scenarios are then designed and analyzed in detail aiming at medium-and low-speed lane-change conditions.Additionally,in contrast with most research,dynamic trajectory planning which considers the possible state variations of the surrounding vehicles and the driver characteristics is studied and described by a fifth-order polynomial function.The safety and comfort of the dynamic trajectory planning are validated through simulation.Moreover,the elastic soft constraint of the safety domain is designed,whereby the sensitivity of the studied dynamic trajectory planning system is reduced under the premise of ensuring safety.The effectiveness of the elastic soft constraint in terms of improving comfort during the lane change is verified through simulation.The availability of the dynamic trajectory planning system with the elastic soft constraint is demonstrated with the addition of trajectory tracking based on model predictive control,showing its potential in practical applications.

Real-time trajectory planning for UCAV air-to-surface attack using inverse dynamics optimization method and receding horizon control

This paper presents a computationally efficient real-time trajectory planning framework for typical unmanned combat aerial vehicle （UCAV） performing autonomous air-to-surface （A/S） attack. It combines the benefits of inverse dynamics optimization method and receding horizon optimal control technique. Firstly, the ground attack trajectory planning problem is mathematically formulated as a receding horizon optimal control problem （RHC-OCP）. In particular, an approximate elliptic launch acceptable region （LAR） model is proposed to model the critical weapon delivery constraints. Secondly, a planning algorithm based on inverse dynamics optimization, which has high computational efficiency and good convergence properties, is developed to solve the RHCOCP in real-time. Thirdly, in order to improve robustness and adaptivity in a dynamic and uncer- tain environment, a two-degree-of-freedom （2-DOF） receding horizon control architecture is introduced and a regular real-time update strategy is proposed as well, and the real-time feedback can be achieved and the not-converged situations can be handled. Finally, numerical simulations demon- strate the efficiency of this framework, and the results also show that the presented technique is well suited for real-time implementation in dynamic and uncertain environment.

Intelligent and Autonomous Flight Technology for Launch Vehicles

This paper proposes the architecture of an intelligent flight launcher system as well as fundamental solutions to capability prediction and dynamic planning. This effort reflects the latest progress in the applications of intelligent and autonomous technology for launcher flights. The paper first describes the characteristics and capabilities of intelligent and autonomous systems and classifies various related technologies. In the context of intelligent and autonomous technology in aerospace engineering, it then focuses on technical difficulties involved with intelligent flight and reviews developments in the field. An E^3 classification model of an intelligent flight launcher is then proposed and its application scenarios are discussed. Based on an intelligent flight system configuration of the launcher, the online trajectory planning and initial value guess are examined, and vertical landing is provided as an example to explain the effects of the implementation of computational intelligence to flight systems.

Mechanical Design and Dynamic Compliance Control of Lightweight Manipulator

In the existing modular joint design and control methods of collaborative robots, the inertia of the manipulator link is large,the dynamic trajectory planning ability is weak, the collision stop safety strategy is dependent, and the adaptability and safety to the changing environment are limited. This paper develops a six-degree-of-freedom lightweight collaborative manipulator with real-time dynamic trajectory planning and active compliance control. Firstly, a novel motor installation, joint transmission, and link design method is put forward to reduce the inertia of the links and improve intrinsic safety. At the same time, to enhance the dynamic operation capability and quick response of the manipulator, a smooth planning of position and orientation under initial/end pose and velocity constraints is proposed. The adaptability to the environment is improved by the active compliance control. Finally, experiments are carried out to verify the effectiveness of the proposed design, planning, and control methods.