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Collision avoidance

About: Collision avoidance is a research topic. Over the lifetime, 8014 publications have been published within this topic receiving 111414 citations.


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Journal ArticleDOI
TL;DR: There are various routing techniques, real‐time applications of UAVs which are elaborated in this paper, namely, representative, cooperative, and noncooperative techniques, and collision avoidance techniques which are very important for the obstacle‐free environment.

112 citations

Journal ArticleDOI
TL;DR: A new risk assessment based decision-making algorithm to guarantee collision avoidance in multi-scenarios for autonomous vehicles with adjustable driving style preferences to meet the demand of different consumers would improve drivers’ acceptance of autonomous vehicles.
Abstract: In this paper, we proposed a new risk assessment based decision-making algorithm to guarantee collision avoidance in multi-scenarios for autonomous vehicles. A probabilistic-model based situation assessment module using conditional random field was proposed to assess the risk level of surrounding traffic participants. Based on the assessed risk from the situation assessment module, a collision avoidance strategy with driving style preferences (e.g., aggressive or conservative) was proposed to meet the demands of different drivers or passengers. Finally, we conducted experiments in Carla (car learning to act) to evaluate our developed collision avoidance decision-making algorithm in different scenarios. The results show that our developed method was sufficiently reliable for autonomous vehicles to avoid collisions in multi-scenarios with different driving style preferences. Our developed method with adjustable driving style preferences to meet the demand of different consumers would improve drivers’ acceptance of autonomous vehicles.

111 citations

Journal ArticleDOI
TL;DR: The proposed strategies allow a group of UAVs to avoid obstacles and separate if necessary through a simple algorithm with low computation by expanding the collision-cone approach to formation of Uavals.
Abstract: Collision avoidance strategies for multiple unmanned aerial vehicles (UAVs) based on geometry are investigated in this study. The proposed strategies allow a group of UAVs to avoid obstacles and separate if necessary through a simple algorithm with low computation by expanding the collision-cone approach to formation of UAVs. The geometric approach uses line-of-sight vectors and relative velocity vectors where dynamic constraints are included in the formation. Each UAV can determine which plane and direction are available for collision avoidance. An analysis is performed to define an envelope for collision avoidance, where angular rate limits and obstacle detection range limits are considered. Based on the collision avoidance envelope, each UAV in a formation determines whether the formation can be maintained or not while avoiding obstacles. Numerical simulations are performed to demonstrate the performance of the proposed strategies.

111 citations

Proceedings ArticleDOI
10 Apr 2007
TL;DR: This work has developed a method of collision avoidance that can be used in three dimensions in much the same way as autonomous ground vehicles that navigate over unexplored terrain that safely avoids large objects like buildings and trees but also wires as thin as 6 mm.
Abstract: Safe autonomous flight is essential for widespread acceptance of aircraft that must fly close to the ground. We have developed a method of collision avoidance that can be used in three dimensions in much the same way as autonomous ground vehicles that navigate over unexplored terrain. Safe navigation is accomplished by a combination of online environmental sensing, path planning and collision avoidance. Here we report results with an autonomous helicopter that operates at low elevations in uncharted environments some of which are densely populated with obstacles such as buildings, trees and wires. We have recently completed over 1000 successful runs in which the helicopter traveled between coarsely specified waypoints separated by hundreds of meters, at speeds up to 10 meters/sec at elevations of 5-10 meters above ground level. The helicopter safely avoids large objects like buildings and trees but also wires as thin as 6 mm. We believe this represents the first time an air vehicle has traveled this fast so close to obstacles. Here we focus on the collision avoidance method that learns to avoid obstacles by observing the performance of a human operator.

110 citations

Book ChapterDOI
01 Jan 1986
TL;DR: In this article, the manipulator control problem is reformulated in terms of direct control of manipulator motion in operational space, the space in which the task is originally described, rather than controlling the task's corresponding joint space motion obtained after geometric and kinematic transformation.
Abstract: The paper presents a radically new approach to real-time dynamic control and active force control of manipulators In this approach the manipulator control problem is reformulated in terms of direct control of manipulator motion in operational space, the space in which the task is originally described, rather than controlling the task’s corresponding joint space motion obtained after geometric and kinematic transformation The control method is based on the construction of the manipulator end effector dynamic model in operational space Also, the paper presents a unique real-time obstacle avoidance method for manipulators and mobile robots based on the “artificial potential field” concept In this method, collision avoidance, traditionally considered a high level planning problem, can be effectively distributed between different levels of control, allowing real-time robot operations in a complex environment Using a time-varying artificial potential field, this technique has been extended to moving obstacles A two-level control architecture has been designed to increase the system real-time performance These methods have been implemented in the COSMOS system for a PUMA 560 robot arm We have demonstrated compliance, contact, sliding, and insertion operations using wrist and finger sensing, as well as real-time collision avoidance with moving obstacles using visual sensing

110 citations


Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20242
2023547
20221,269
2021503
2020621
2019661