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.

Formation Obstacle Avoidance: A Fluid-Based Solution

Abstract: To enhance the mission success rate, the multi-agent system (MAS) often adopts a formation form to shuttle over complex terrain. Compared with obstacle avoidance in other multi-agent coordinated missions, multi-agent formation (MAF) obstacle avoidance is more challenging because agents must both avoid obstacles and subsequently return to their intended positions in the original formation at a uniform speed. Aiming at the three-dimensional complex obstacle environment, the fluid methodology is extended to the application of the formation issue for the first time. In this paper, an MAF obstacle avoidance framework built upon model-based interfered fluid dynamical system (MIFDS), which is the most representative algorithm in fluid methodology, is proposed. The proposed MIFDS is modified to be more in accordance with the kinematic performance of agents than traditional IFDS by introducing the kinematic model and constraints. Moreover, on the basis of MIFDS and the virtual leader formation structure, a novel original fluid speed adjustment strategy in MIFDS, which is the core to solve the formation issue, is designed to balance obstacle avoidance and formation reconfiguration. Finally, receding horizon control is introduced to further guarantee the performance of obstacle avoidance and motion safety. Simulations are used to demonstrate the effectiveness of the proposed method.

Aerial Obstacle Detection With 3 - D Mobile Devices

Abstract: In this paper, we present a novel approach for aerial obstacle detection (e.g., branches or awnings) using a 3-D smartphone in the context of the visually impaired (VI) people assistance. This kind of obstacles are especially challenging because they cannot be detected by the walking stick or the guide dog. The algorithm captures the 3-D data of the scene through stereo vision. To our knowledge, this is the first work that presents a technology able to obtain real 3-D measures with smartphones in real time. The orientation sensors of the device (magnetometer and accelerometer) are used to approximate the walking direction of the user, in order to look for the obstacles only in such a direction. The obtained 3-D data are compressed and then linearized for detecting the potential obstacles. Potential obstacles are tracked in order to accumulate enough evidence to alert the user only when a real obstacle is found. In the experimental section, we show the results of the algorithm in several situations using real data and helped by VI users.

Display apparatus for a vehicle

Abstract: For displaying a virtual image without hindering from seeing a front view, a display apparatus for a vehicle includes a storage device 21 b for storing a distance information of superimposed viewing, the distance information indicating a distance between an obstacle in the view ahead a vehicle and the vehicle when the obstacle and, a virtual image of a picture projected on a windshield are viewed as a superimposed front view; distance measuring means 40 for measuring a distance between the vehicle and the obstacle; judging means 21 a 1 for judging whether or not the virtual image is superimposed on the obstacle; and control means 21 a 2 for stopping the projection of the virtual image when it is judged that the virtual image is superimposed on the obstacle.

Pseudospectral motion planning techniques for autonomous obstacle avoidance

Abstract: We consider the problem of generating minimum- time trajectories for autonomous vehicles. Shapes of arbitrary number, size and configuration are modeled in the form of path constraints in the resulting constrained nonlinear optimal control problem. Pseudospectral techniques are used to solve the problem. Solutions are obtained within a few seconds even under a MATLAB environment running on legacy computer hardware. The method is tested under various obstacle environments, and the optimality of the computed trajectories is verified by way of the necessary conditions.

A Monocular Vision Sensor-Based Obstacle Detection Algorithm for Autonomous Robots

Abstract: This paper presents a monocular vision sensor-based obstacle detection algorithm for autonomous robots. Each individual image pixel at the bottom region of interest is labeled as belonging either to an obstacle or the floor. While conventional methods depend on point tracking for geometric cues for obstacle detection, the proposed algorithm uses the inverse perspective mapping (IPM) method. This method is much more advantageous when the camera is not high off the floor, which makes point tracking near the floor difficult. Markov random field-based obstacle segmentation is then performed using the IPM results and a floor appearance model. Next, the shortest distance between the robot and the obstacle is calculated. The algorithm is tested by applying it to 70 datasets, 20 of which include nonobstacle images where considerable changes in floor appearance occur. The obstacle segmentation accuracies and the distance estimation error are quantitatively analyzed. For obstacle datasets, the segmentation precision and the average distance estimation error of the proposed method are 81.4% and 1.6 cm, respectively, whereas those for a conventional method are 57.5% and 9.9 cm, respectively. For nonobstacle datasets, the proposed method gives 0.0% false positive rates, while the conventional method gives 17.6%.