Adaptive neuro-NMPC control of redundant robotic manipulators for path tracking and obstacle avoidance

2009 ◽  
Author(s):  
A. M. Z. Jasour ◽  
M. Farrokhi
Keyword(s):  
Obstacle Avoidance ◽  
Robotic Manipulators ◽  
Path Tracking

LENGTH-OPTIMIZED SMOOTH OBSTACLE AVOIDANCE FOR ROBOTIC MANIPULATORS

2011 ◽  
Vol 35 (4) ◽  
pp. 505-514 ◽  
Author(s):  
Soheil S. Parsa ◽  
Juan A. Carretero ◽  
Roger Boudreau
Keyword(s):  
Harmonic Function ◽  
Obstacle Avoidance ◽  
Robotic Manipulators ◽  
Joint Space ◽  
Displacement Velocity ◽  
End Effector ◽  
Smooth Path ◽  
Simulation Results

This paper presents a novel optimized smooth obstacle avoidance algorithm for robotic manipulators. First, a 3-4-5 interpolating polynomial is used to plan a smooth trajectory between initial and final positions in the joint space without considering any obstacles. Then, a simple harmonic function, which is smooth and continuous in displacement, velocity and acceleration, is applied to generate a new smooth path avoiding collisions between the robot links and an obstacle. The obstacle avoidance portions on the path are optimized such that the length of the path traversed by the end-effector is minimized. Simulation results for a 6 DOF serial manipulator demonstrate the efficiency of the proposed method.

Fuzzy control for path tracking and obstacle avoidance of a qudrotor flight

2015 ◽  
Author(s):  
M. H. Sabour ◽  
A. Kosari ◽  
Farhad Ahadi Koloo ◽  
K. Shamsi ◽  
Morteza Mohammadzaheri
Keyword(s):  
Fuzzy Control ◽  
Obstacle Avoidance ◽  
Path Tracking

scholarly journals A HEURISTIC CASCADING FUZZY LOGIC APPROACH TO REACTIVE NAVIGATION FOR UAV

2014 ◽  
Vol 15 (2) ◽  
Author(s):  
Yew-Chung Chak ◽  
Renuganth Varatharajoo
Keyword(s):  
Fuzzy Logic ◽  
Obstacle Avoidance ◽  
Control Strategy ◽  
Tracking Control ◽  
Path Tracking ◽  
Reactive Navigation ◽  
Logic Control ◽  
Fuzzy Logic Approach ◽  
Avoidance Control ◽  
Logic Approach

ABSTRACT: The capability of navigating Unmanned Aerial Vehicles (UAVs) safely in unknown terrain offers huge potential for wider applications in non-segregated airspace. Flying in non-segregated airspace present a risk of collision with static obstacles (e.g., towers, power lines) and moving obstacles (e.g., aircraft, balloons). In this work, we propose a heuristic cascading fuzzy logic control strategy to solve for the Conflict Detection and Resolution (CD&R) problem, in which the control strategy is comprised of two cascading modules. The first one is Obstacle Avoidance control and the latter is Path Tracking control. Simulation results show that the proposed architecture effectively resolves the conflicts and achieve rapid movement towards the target waypoint.ABSTRAK: Keupayaan mengemudi Kenderaan Udara Tanpa Pemandu (UAV) dengan selamat di kawasan yang tidak diketahui menawarkan potensi yang besar untuk aplikasi yang lebih luas dalam ruang udara yang tidak terasing. Terbang di ruang udara yang tidak terasing menimbulkan risiko perlanggaran dengan halangan statik (contohnya, menara, talian kuasa) dan halangan bergerak (contohnya, pesawat udara, belon). Dalam kajian ini, kami mencadangkan satu strategi heuristik kawalan logik kabur yang melata untuk menyelesaikan masalah Pengesanan Konflik dan Penyelesaian (CD&R), di mana strategi kawalan yang terdiri daripada dua modul melata. Hasil simulasi menunjukkan bahawa seni bina yang dicadangkan berjaya menyelesaikan konflik dan mencapai penerbangan pesat ke arah titik laluan sasaran.KEYWORDS: fuzzy logic; motion planning; obstacle avoidance; path tracking; reactive navigation; UAV

Time-optimal path tracking for robots under dynamics constraints based on convex optimization

Robotica ◽  
2015 ◽  
Vol 34 (9) ◽  
pp. 2116-2139 ◽  
Author(s):  
Qiang Zhang ◽  
Shurong Li ◽  
Jian-Xin Guo ◽  
Xiao-Shan Gao
Keyword(s):  
Convex Optimization ◽  
High Speed ◽  
Optimal Path ◽  
Robotic Manipulators ◽  
Path Tracking ◽  
Minimum Time ◽  
Linear Functions ◽  
Change Rate ◽  
Time Path ◽  
Motion Time

SUMMARYTo fully utilize the dynamic performance of robotic manipulators and enforce minimum motion time in path tracking, the problem of minimum time path tracking for robotic manipulators under confined torque, change rate of the torque, and voltage of the DC motor is considered. The main contribution is the introduction of the concepts of virtual change rate of the torque and the virtual voltage, which are linear functions in the state and control variables and are shown to be very tight approximation to the real ones. As a result, the computationally challenging non-convex minimum time path tracking problem is reduced to a convex optimization problem which can be solved efficiently. It is also shown that introducing dynamics constraints can significantly improve the motion precision without costing much in motion time, especially in the case of high speed motion. Extensive simulations are presented to demonstrate the effectiveness of the proposed approach.

scholarly journals Steering control based on model predictive control for obstacle avoidance of unmanned ground vehicle

2020 ◽  
Vol 53 (3-4) ◽  
pp. 501-518
Author(s):  
Chaofang Hu ◽  
Lingxue Zhao ◽  
Lei Cao ◽  
Patrick Tjan ◽  
Na Wang
Keyword(s):  
Path Planning ◽  
Model Predictive Control ◽  
Obstacle Avoidance ◽  
Predictive Control ◽  
Path Tracking ◽  
Unmanned Ground Vehicle ◽  
Steering Control ◽  
Steering Angle ◽  
Ground Vehicle ◽  
Tracking Controller

In this paper, a strategy based on model predictive control consisting of path planning and path tracking is designed for obstacle avoidance steering control problem of the unmanned ground vehicle. The path planning controller can reconfigure a new obstacle avoidance reference path, where the constraint of the front-wheel-steering angle is transformed to formulate lateral acceleration constraint. The path tracking controller is designed to realize the accurate and fast following of the reconfigured path, and the control variable of tracking controller is steering angle. In this work, obstacles are divided into two categories: static and dynamic. When the decision-making system of the unmanned ground vehicle determines the existence of static obstacles, the obstacle avoidance path will be generated online by an optimal path reconfiguration based on direct collocation method. In the case of dynamic obstacles, receding horizon control is used for real-time path optimization. To decrease online computation burden and realize fast path tracking, the tracking controller is developed using the continuous-time model predictive control algorithm, where the extended state observer is combined to estimate the lumped disturbances for strengthening the robustness of the controller. Finally, simulations show the effectiveness of the proposed approach in comparison with nonlinear model predictive control, and the CarSim simulation is presented to further prove the feasibility of the proposed method.

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