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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.


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Journal ArticleDOI
TL;DR: This paper addresses the problem of humanoid robots stepping over obstacles with a focus on feasibility analysis and motion planning and presents an algorithm to generate suitable trajectories of the feet and the waist of the robot using heuristic methodology.
Abstract: The wide potential applications of humanoid robots require that the robots can walk in complex environments and overcome various obstacles. To this end, we address the problem of humanoid robots stepping over obstacles in this paper. We focus on two aspects, which are feasibility analysis and motion planning. The former determines whether a robot can step over a given obstacle, and the latter discusses how to step over, if feasible, by planning appropriate motions for the robot. We systematically examine both of these aspects. In the feasibility analysis, using an optimization technique, we cast the problem into global optimization models with nonlinear constraints, including collision-free and balance constraints. The solutions to the optimization models yield answers to the possibility of stepping over obstacles under some assumptions. The presented approach for feasibility provides not only a priori knowledge and a database to implement stepping over obstacles, but also a tool to evaluate and compare the mobility of humanoid robots. In motion planning, we present an algorithm to generate suitable trajectories of the feet and the waist of the robot using heuristic methodology, based on the results of the feasibility analysis. We decompose the body motion of the robot into two parts, corresponding to the lower body and upper body of the robot, to meet the collision-free and balance constraints. This novel planning method is adaptive to obstacle sizes, and is, hence, oriented to autonomous stepping over by humanoid robots guided by vision or other range finders. Its effectiveness is verified by simulations and experiments on our humanoid platform HRP-2

49 citations

Proceedings ArticleDOI
05 Dec 1990
TL;DR: An approach to mobile robot navigation that unifies the problems of obstacle avoidance, position estimation, and map building in a common multi-target tracking framework and an implementation of model-based localization that achieves robust position estimation in a known environment is presented.
Abstract: The authors describe an approach to mobile robot navigation that unifies the problems of obstacle avoidance, position estimation, and map building in a common multi-target tracking framework. Model-based navigation is viewed as a process of tracking naturally occurring geometric targets or beacons. Targets that have been predicted (expected) from the environment map are tracked to provide vehicle position estimates (localization). Targets that are observed, but not predicted, represent unknown environment features or obstacles and cause new tracks to be initiated, classified, and ultimately integrated into the map. A good sensor model is a crucial component of this approach, and is used both for predicting expected observations and classifying unexpected observations. This navigation framework is being implemented on a mobile robot that employs sonar as the principal navigation sensor. An implementation of model-based localization that achieves robust position estimation in a known environment is presented. Preliminary results in obstacle identification and map building are given that lead one to believe that a complete navigation system, encompassing localization, obstacle avoidance, and map building, can be implemented exclusively with sonar. >

49 citations

Journal ArticleDOI
01 Apr 2010
TL;DR: In this paper, the authors present a method for trajectory generation using convex optimization to find a feasible, obstacle-free path for a road vehicle, considering vehicle rotation and obstacle avoidance.
Abstract: This paper presents a method for trajectory generation using convex optimization to find a feasible, obstacle-free path for a road vehicle. Consideration of vehicle rotation is shown to be necessary if the trajectory is to avoid obstacles specified in a fixed Earth axis system. The paper establishes that, despite the presence of significant non-linearities, it is possible to articulate the obstacle avoidance problem in a tractable convex form using multiple optimization passes. Finally, it is shown by simulation that an optimal trajectory that accounts for the vehicle's changing velocity throughout the manoeuvre is superior to a previous analytical method that assumes constant speed.

49 citations

Journal ArticleDOI
14 May 2014
TL;DR: This article proposes an experimental platform, which performs obstacle detection, risk assessment and path planning (avoidance) tasks autonomously in an integrated manner, and demonstrates that the proposed system can be useful for both uninhabited and manned vessels.
Abstract: Unmanned surface vehicles are becoming increasingly vital tools in a variety of maritime applications. Unfortunately, their usability is severely constrained by the lack of a reliable obstacle detection and avoidance system. In this article, one such experimental platform is proposed, which performs obstacle detection, risk assessment and path planning (avoidance) tasks autonomously in an integrated manner. The detection system is based on a vision-LIDAR (light detection and ranging) system, whereas a heuristic path planner is utilised. A unique property of the path planner is its compliance with the marine collision regulations. It is demonstrated through hardware-in-the-loop simulations that the proposed system can be useful for both uninhabited and manned vessels.

49 citations

Proceedings ArticleDOI
09 Apr 1991
TL;DR: In this article, several schemes for obstacle detection for autonomous vehicles traveling at high speeds (about 5 m/s) are presented. But they make a globally flat-world assumption and ignore vehicle pitch motion.
Abstract: Several schemes are presented for obstacle detection for autonomous vehicles traveling at high speeds (about 5 m/s). In particular, the authors discuss schemes that make a globally flat-world assumption and ignore vehicle pitch motion. They examine methods that relax the above assumptions. In each case the strengths and weaknesses of the solutions proposed are discussed. Experimental and simulation results are presented. >

49 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