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Obstacle

About: Obstacle is a research topic. Over the lifetime, 9517 publications have been published within this topic receiving 94760 citations. The topic is also known as: impediment & barrier.


Papers
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Proceedings ArticleDOI
04 Jun 2008
TL;DR: After detecting a dynamic obstacle, the approach exploits structure in the environment where possible to generate a set of likely hypotheses for the future behavior of the obstacle and efficiently incorporates these hypotheses into the planning process to produce safe actions.
Abstract: We present an approach for robust detection, prediction, and avoidance of dynamic obstacles in urban environments. After detecting a dynamic obstacle, our approach exploits structure in the environment where possible to generate a set of likely hypotheses for the future behavior of the obstacle and efficiently incorporates these hypotheses into the planning process to produce safe actions. The techniques presented are very general and can be used with a wide range of sensors and planning algorithms. We present results from an implementation on an autonomous passenger vehicle that has traveled thousands of miles in populated urban environments and won first place in the DARPA Urban Challenge.

143 citations

Journal ArticleDOI
TL;DR: In this paper, the effect of using different obstacles on thermal stratification in a cylindrical hot water tank is analyzed numerically using both experimental and numerical results, and the results indicate that placing obstacle in the tank provides better thermal stratified compared to the no obstacle case.

143 citations

Patent
07 Jul 1994
TL;DR: In this paper, an obstacle detection system for an automotive vehicle detects obstacles ahead of the vehicle and finds the dynamic relativity between the vehicle between each obstacle and each of the obstacles, based on which information relating to a danger level between vehicle and each obstacle is operated on so as to make a danger judgement.
Abstract: An obstacle detection system for an automotive vehicle detects obstacles ahead of the vehicle and finds the dynamic relativity between the vehicle and each of the obstacles. Based on the dynamic relativity, information relating to a danger level between the vehicle and each obstacle is operated on so as to make a danger judgement. A frequency, at which the operations on the information relating to danger level are made, is increasingly or decreasingly varied according to the danger levels of the obstacles.

139 citations

Journal ArticleDOI
TL;DR: A bounded control law for nonholonomic systems of unicycle-type is reported on that satisfactorily drive a vehicle along a desired trajectory while guaranteeing a minimum safe distance from another vehicle or obstacle at all times.
Abstract: Nowadays, autonomously operated nonholonomic vehicles are employed in a wide range of applications, ranging from relatively simple household chores (e.g. carpet vacuuming and lawn mowing) to highly sophisticated assignments (e.g. outer space exploration and combat missions). Each application may require different levels of accuracy and capabilities from the vehicles, yet, all expect the same critical outcome: to safely complete the task while avoiding collisions with obstacles and the environment. Herein, we report on a bounded control law for nonholonomic systems of unicycle-type that satisfactorily drive a vehicle along a desired trajectory while guaranteeing a minimum safe distance from another vehicle or obstacle at all times. The control law is comprised of two parts. The first is a trajectory tracking and set-point stabilization control law that accounts for the vehicle's kinematic and dynamic constraints (i.e. restrictions on velocity and acceleration). We show that the bounded tracking control law enforces global asymptotic convergence to the desired trajectory and local exponential stability of the full state vector in the case of set-point stabilization. The second part is a real-time avoidance control law that guarantees collision-free transit for the vehicle in noncooperative and cooperative scenarios independently of bounded uncertainties and errors in the obstacles' detection process. The avoidance control acts locally, meaning that it is only active when an obstacle is close and null when the obstacle is safely away. Moreover, the avoidance control is designed according to the vehicle's acceleration limits to compensate for lags in the vehicle's reaction time. The performance of the synthesized control law is then evaluated and validated via simulation and experimental tests.

135 citations

Proceedings ArticleDOI
18 Apr 2005
TL;DR: A vision-based obstacle detection system for small unmanned aerial vehicles (UAVs) is presented and the feasibility of this approach is demonstrated by using the vision output to steer a small unmanned aircraft to fly towards an obstacle.
Abstract: A vision-based obstacle detection system for small unmanned aerial vehicles (UAVs) is presented. Obstacles are detected by segmenting the image into sky and non-sky regions and treating the non-sky regions as obstacles. The feasibility of this approach is demonstrated by using the vision output to steer a small unmanned aircraft to fly towards an obstacle. The experiment was first verified in a hardware in the loop (HIL) simulation and then successfully implemented on a small modified remote control plane using a large inflatable balloon as the obstacle.

135 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20241
20231,483
20223,389
2021407
2020817
2019873