scholarly journals Obstacle Avoidance Control for Multisteering Mode of Multiaxle Wheeled Robot Based on Trajectory Prediction Strategy

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yongqiang Zhu ◽  
Junru Zhu ◽  
Pingxia Zhang
Keyword(s):  
Obstacle Avoidance ◽  
Control Strategy ◽  
Trajectory Prediction ◽  
Coverage Area ◽  
Iterative Calculation ◽  
Wheeled Robot ◽  
Avoidance Control ◽  
Narrow Space ◽  
The Relationship ◽  
Prediction Strategy

A multiaxle wheeled robot is difficult to be controlled due to its long body and a large number of axles, especially for obstacle avoidance and steering in narrow space. To solve this problem, a multisteering mode control strategy based on front and rear virtual wheels is proposed, and the driving trajectory prediction of the multiaxle wheeled robot is analyzed. On this basis, an obstacle avoidance control strategy based on trajectory prediction is proposed. By calculating the relationship between the lidar points of the obstacle and the trajectory coverage area, the iterative calculation of the obstacle avoidance scheme for the proposed steering is carried out, and the feasible obstacle avoidance scheme is obtained. The mechanical structure, hardware, and software control system of a five-axle wheeled robot are designed. Finally, to verify the effectiveness of the obstacle avoidance strategy, a Z-shaped obstacle avoidance experiment was carried out. The results confirm the effectiveness of the proposed control strategy.

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

scholarly journals Emergency collision avoidance control strategy based on four-wheel steering and differential braking

2021 ◽  
Author(s):  
Haiqing Li ◽  
Yongfu Li ◽  
Taixiong Zheng ◽  
Jiufei Luo ◽  
Zonghuan Guo
Keyword(s):  
Collision Avoidance ◽  
Obstacle Avoidance ◽  
Control Strategy ◽  
Tracking Control ◽  
Development Trend ◽  
Path Tracking ◽  
Intelligent Vehicles ◽  
Control Mode ◽  
Avoidance Control ◽  
Driving Stability

Abstract Path tracking control strategy of emergency collision avoidance is the research hotspot for intelligent vehicles, and active four-wheel steering and integrated chassis control such as differential braking are the development trend for the control system of intelligent vehicle. Considering both driving performance and path tracking performance, an active obstacle avoidance controller integrated with four-wheel steering (4WS), active rear steering (ARS) and differential braking control (RBC) based on adaptive model predictive theory (AMPC) is proposed. The designed active obstacle avoidance control architecture is composed of two parts, a supervisor and an MPC controller. The supervisor is responsible for selecting the appropriate control mode based on driving vehicle information and threshold of lateral and roll stability. In addition, a non-linear predict model is employed to obtain the future states of the driving vehicle. Then the AMPC is used to calculate the desired steering angle and differential braking toque when the driving stability indexes exceed the safety threshold. Finally, the proposed collision avoidance path tracking control strategy was simulated under emergency conditions via Carsim-Simulink co-simulation. The results show that the controller based on AMPC can be used to tracking the path of obstacle avoidance and has good performance in driving stability under emergencies.

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