scholarly journals Analysis of Collision Threat Parameters and Criteria

2015 ◽  
Vol 68 (5) ◽  
pp. 887-896 ◽  
Author(s):  
Andrzej S. Lenart
Keyword(s):  
Collision Avoidance ◽  
Safe Distance ◽  
Dangerous Situation ◽  
Special Cases

In this paper collision threat parameters such as the distance at closest point of approach and time to the closest point of approach are derived and analysed for special cases and features; collision criteria are analysed for limitations. A new collision threat parameter - time to safe distance - is proposed and its different applications to collision avoidance are presented. Time to safe distance can replace time to the closest point of approach, as it gives a safer time in a dangerous situation. It can be applied in Automatic Radar Plotting Aids (ARPAs) to detect dangerous objects and to display possible evasive manoeuvres.

scholarly journals Autonomous and Safe Navigation of Mobile Robots in Vineyard with Smooth Collision Avoidance

Agriculture ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 954
Author(s):  
Abhijeet Ravankar ◽  
Ankit A. Ravankar ◽  
Arpit Rawankar ◽  
Yohei Hoshino
Keyword(s):  
Mobile Robots ◽  
Real Time ◽  
Collision Avoidance ◽  
Autonomous Navigation ◽  
Autonomous Robots ◽  
Robot Navigation ◽  
Indoor Environments ◽  
Safe Distance ◽  
Field Robots ◽  
Safe Navigation

In recent years, autonomous robots have extensively been used to automate several vineyard tasks. Autonomous navigation is an indispensable component of such field robots. Autonomous and safe navigation has been well studied in indoor environments and many algorithms have been proposed. However, unlike structured indoor environments, vineyards pose special challenges for robot navigation. Particularly, safe robot navigation is crucial to avoid damaging the grapes. In this regard, we propose an algorithm that enables autonomous and safe robot navigation in vineyards. The proposed algorithm relies on data from a Lidar sensor and does not require a GPS. In addition, the proposed algorithm can avoid dynamic obstacles in the vineyard while smoothing the robot’s trajectories. The curvature of the trajectories can be controlled, keeping a safe distance from both the crop and the dynamic obstacles. We have tested the algorithm in both a simulation and with robots in an actual vineyard. The results show that the robot can safely navigate the lanes of the vineyard and smoothly avoid dynamic obstacles such as moving people without abruptly stopping or executing sharp turns. The algorithm performs in real-time and can easily be integrated into robots deployed in vineyards.

Research on Collision Avoidance Method of Car Anti-Head-and-Rear Based on Safe Distance Model

2011 ◽  
Vol 243-249 ◽  
pp. 4435-4440 ◽  
Author(s):  
Zhong Liang Sun ◽  
Xiao Kan Wang ◽  
Shou Xiang Zai
Keyword(s):  
Collision Avoidance ◽  
Information Acquisition ◽  
Influence Factors ◽  
Safe Distance ◽  
The Road ◽  
Distance Model ◽  
Speed Change ◽  
Collision Avoidance System ◽  
On The Road ◽  
Real Time Information

The present rear-end collision accident proportion on the road increases day after day, car collision avoidance system is more and more paid attention. Analysising the existing car collision avoidance system, we propose a car anti-collision algorithm based on safe distance model in this paper. This method takes the influence factors of safety distance for main parameters which fully considers the speed change and the acceleration change of the car 1 and the car 2. It may realize real-time information acquisition and warning judgment according to the state of car 2, the car could automatic braking if necessary. VB simulation shows that the algorithm can effectively avoid collision, also automatically maintain the distance between vehicles, and lay a foundation for further research on the unmanned car.

scholarly journals Adaptive Safe Distance Prediction Using MPC for Bridge Cranes Considering Anti-Swing in Dynamic Environment

2020 ◽  
Author(s):  
Huili Chen ◽  
Guoliang Liu ◽  
Guohui Tian ◽  
Jianhua Zhang ◽  
Ze Ji
Keyword(s):  
Dynamic Environment ◽  
Prediction Method ◽  
Bridge Crane ◽  
Safe Distance ◽  
Moving Obstacles ◽  
Dangerous Situation ◽  
The Mean ◽  
Prediction Control ◽  
Distance Prediction ◽  
Mean Time

<div>In dynamic environment, the suddenly appeared </div><div>human or other moving obstacles can affect the safety of the </div><div>bridge crane. For such dangerous situation, the bridge crane </div><div>must predict potential collisions between the payload and the </div><div>obstacle, keep safe distance while the swing of the payload must </div><div>be considered in the mean time. Therefore, the safe distance is </div><div>not a constant value, which must be adaptive to the relative </div><div>speed of the bridge crane. However, as far as we know, the </div><div>mathematical model between the safe distance and the relative </div><div>speed of the bridge crane has never been fully discussed. In </div><div>this paper, we propose a safe distance prediction method using </div><div>model prediction control (MPC), which can make sure that the </div><div>crane can stop before the obstacle, and avoid possible collisions, </div><div>while the relative speed and anti-swing are both considered. The </div><div>experimental results prove the effectiveness of our idea.</div>

scholarly journals Adaptive Safe Distance Prediction Using MPC for Bridge Cranes Considering Anti-Swing in Dynamic Environment

2020 ◽  
Author(s):  
Huili Chen ◽  
Guoliang Liu ◽  
Guohui Tian ◽  
Jianhua Zhang ◽  
Ze Ji
Keyword(s):  
Dynamic Environment ◽  
Prediction Method ◽  
Bridge Crane ◽  
Safe Distance ◽  
Moving Obstacles ◽  
Dangerous Situation ◽  
The Mean ◽  
Prediction Control ◽  
Distance Prediction ◽  
Mean Time

<div>In dynamic environment, the suddenly appeared </div><div>human or other moving obstacles can affect the safety of the </div><div>bridge crane. For such dangerous situation, the bridge crane </div><div>must predict potential collisions between the payload and the </div><div>obstacle, keep safe distance while the swing of the payload must </div><div>be considered in the mean time. Therefore, the safe distance is </div><div>not a constant value, which must be adaptive to the relative </div><div>speed of the bridge crane. However, as far as we know, the </div><div>mathematical model between the safe distance and the relative </div><div>speed of the bridge crane has never been fully discussed. In </div><div>this paper, we propose a safe distance prediction method using </div><div>model prediction control (MPC), which can make sure that the </div><div>crane can stop before the obstacle, and avoid possible collisions, </div><div>while the relative speed and anti-swing are both considered. The </div><div>experimental results prove the effectiveness of our idea.</div>

scholarly journals An Efficient Ship Automatic Collision Avoidance Method Based on Modified Artificial Potential Field

2021 ◽  
Vol 10 (1) ◽  
pp. 3
Author(s):  
Zhongxian Zhu ◽  
Hongguang Lyu ◽  
Jundong Zhang ◽  
Yong Yin
Keyword(s):  
Collision Avoidance ◽  
Potential Field ◽  
Repulsive Force ◽  
Adjustable Parameter ◽  
Artificial Potential Field ◽  
Force Model ◽  
Safe Distance ◽  
International Regulations ◽  
Motion Characteristics ◽  
Approach Time

A novel collision avoidance (CA) algorithm was proposed based on the modified artificial potential field (APF) method, to construct a practical ship automatic CA system. Considering the constraints of both the International Regulations for Preventing Collisions at Sea (COLREGS) and the motion characteristics of the ship, the multi-ship CA algorithm was realized by modifying the repulsive force model in the APF method. Furthermore, the distance from the closest point of approach-time to the closest point of approach (DCPA-TCPA) criterion was selected as the unique adjustable parameter from the perspective of navigation practice. Collaborative CA experiments were designed and conducted to validate the proposed algorithm. The results of the experiments revealed that the actual DCPA and TCPA agree well with the parameter setup that keeps the ship at a safe distance from other ships in complex encountering situations. Consequently, the algorithm proposed in this study can achieve efficient automatic CA with minimal parameter settings. Moreover, the navigators can easily accept and comprehend the adjustable parameters, enabling the algorithm to satisfy the demand of the engineering applications.

scholarly journals ITC: Infused Tangential Curves for Smooth 2D and 3D Navigation of Mobile Robots

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4384 ◽  
Author(s):  
Abhijeet Ravankar ◽  
Ankit Ravankar ◽  
Arpit Rawankar ◽  
Yohei  Hoshino ◽  
Yukinori Kobayashi
Keyword(s):  
Mobile Robots ◽  
Real Time ◽  
Collision Avoidance ◽  
Safe Distance ◽  
3D Navigation ◽  
Aerial Robots ◽  
Mobile Navigation ◽  
Straight Segments ◽  
Complex Scenario ◽  
2D And 3D

Navigation is an indispensable component of ground and aerial mobile robots. Although there is a plethora of path planning algorithms, most of them generate paths that are not smooth and have angular turns. In many cases, it is not feasible for the robots to execute these sharp turns, and a smooth trajectory is desired. We present `ITC: Infused Tangential Curves’ which can generate smooth trajectories for mobile robots. The main characteristics of the proposed ITC algorithm are: (1) The curves are tangential to the path, thus maintaining G 1 continuity, (2) The curves are infused in the original global path to smooth out the turns, (3) The straight segments of the global path are kept straight and only the sharp turns are smoothed, (4) Safety is embedded in the ITC trajectories and robots are guaranteed to maintain a safe distance from the obstacles, (5) The curvature of ITC curves can easily be controlled and smooth trajectories can be generated in real-time, (6) The ITC algorithm smooths the global path on a part-by-part basis thus local smoothing at one point does not affect the global path. We compare the proposed ITC algorithm with traditional interpolation based trajectory smoothing algorithms. Results show that, in case of mobile navigation in narrow corridors, ITC paths maintain a safe distance from both walls, and are easy to generate in real-time. We test the algorithm in complex scenarios to generate curves of different curvatures, while maintaining different safety thresholds from obstacles in vicinity. We mathematically discuss smooth trajectory generation for both 2D navigation of ground robots, and 3D navigation of aerial robots. We also test the algorithm in real environments with actual robots in a complex scenario of multi-robot collision avoidance. Results show that the ITC algorithm can be generated quickly and is suitable for real-world scenarios of collision avoidance in narrow corridors.

scholarly journals Path Planning and Collision Avoidance in Unknown Environments for USVs Based on an Improved D* Lite

2021 ◽  
Vol 11 (17) ◽  
pp. 7863
Author(s):  
Xiaohui Zhu ◽  
Bin Yan ◽  
Yong Yue
Keyword(s):  
Path Planning ◽  
Collision Avoidance ◽  
Autonomous Navigation ◽  
Search Time ◽  
Priority Queue ◽  
Complex Environments ◽  
Safe Distance ◽  
Search Range ◽  
Planning Time ◽  
Unknown Environments

Path planning and collision avoidance during autonomous navigation in unknown environments is a crucial issue for unmanned surface vehicles (USVs). This paper improves the traditional D* Lite algorithm and achieves multi-goal path planning and collision avoidance for USVs in unknown and complex environments. By expanding the adjacent search range and setting a safe distance for USVs, we solve the issue of limited steering maneuverability in USVs with fewer DOF during autonomous navigation. We propose an approach to optimize the planned path during navigation by comparing the estimated distance with the actual distance between the current waypoint and the goal waypoint. A minimum binary heap is used to optimize the priority queue of the D* Lite and significantly reduce the path search time. Simulation results show that the improved D * Lite can significantly reduce the path planning time, optimize the planned path and solve the issue of limited steering maneuverability in USVs. We apply the algorithm to a real USV for further tests. Experimental results show that the USV can plan an optimized path while avoiding both static and dynamic obstacles in complex environments with a safe distance during autonomous navigation.

Sign in / Sign up

Export Citation Format

Share Document