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.

Collision avoidance for mobile robots based on artificial potential field and obstacle envelope modelling

Abstract: Purpose This paper aims to investigate the collision avoidance problem for a mobile robot by constructing an artificial potential field (APF) based on geometrically modelling the obstacles with a new method named the obstacle envelope modelling (OEM). Design/methodology/approach The obstacles of arbitrary shapes are enveloped in OEM using the primitive, which is an ellipse in a two-dimensional plane or an ellipsoid in a three-dimensional space. As the surface details of obstacles are neglected elegantly in OEM, the workspace of a mobile robot is made simpler so as to increase the capability of APF in a clustered environment. Findings Further, a dipole is applied to the construction of APF produced by each obstacle, among which the positive pole pushes the robot away and the negative pole pulls the robot close. Originality/value As a whole, the dipole leads the robot to make a derivation around the obstacle smoothly, which greatly reduces the local minima and trajectory oscillations. Computer simulations are conducted to demonstrate the effectiveness of the proposed approach.

Headlight device for vehicle

Abstract: PURPOSE:To control the light distribution in front of a vehicle so as to recognize an obstacle by a driver of the own vehicle in the running condition. CONSTITUTION:A scope setting process is made to an image taken by a TV camera (200), and after an obstacle detecting process is carried out, the existence of an obstacle is decided (202 and 204). When there is no obstacle, a normal light distribution control to improve the visibility and to prevent a glare is carried out (214). On the other hand, when there is an obstacle, the upper end of the obstacle is measured (206). Then, the position of the cut line by the present shade position is stored (208), and by deciding whether the upper end of the obstacle is near the cut line or not, it is decided whether the normal light distribution control will do or not (210). When the answer is no, a light distribution control to light on the obstacle is carried out (212). By placing the priority to the light distribution to light on the obstacle in such a way, the driver can recognize an obstacle such as a walker securely.

Device for detecting obstacles for a vehicle

Abstract: A device for detecting obstacles for vehicles enables an efficient obstacle detection and improves the accuracy of the detection. The device comprises a section for predicting a derived travel path, on which the vehicle will travel, based on a steering angle, a yaw rate and a speed of the vehicle, a section having a CCD (charge-coupled device) camera for detecting a present travel path, on which the vehicle is moving at present, a radar unit of the scanning type for detecting obstacles in a predetermined region, and a risk potential assessment section for assessing risk potentials of the detected obstacles based on the derived travel path and the present travel path. The risk potential assessment section sets the risk potential in the following way: the obstacle which is detected in a region where the derived travel path and the present travel path overlap each other to the highest risk potential; the obstacle which is detected in a region having the present travel path and without the derived travel path to a medium risk potential; the obstacle which is detected in a region having the derived travel path and without the present travel path to a lower risk potential; and the obstacle which is detected in a region without the present and the derived travel path to the lowest risk potential.

Sensor-Based Motion Planning of Wheeled Mobile Robots in Unknown Dynamic Environments

Abstract: This paper presents a new sensor-based online method for generating collision-free paths for differential-drive wheeled mobile robots pursuing a moving target amidst dynamic and static obstacles. At each iteration, the set of all collision-free directions are calculated using velocity vectors of the robot relative to each obstacle, forming the Directive Circle (DC), which is the fundamental concept of our proposed method. Then, the best feasible direction close to the optimal direction to the target is selected from the DC, which prevents the robot from being trapped in local minima. Local movements of the robot are governed by the exponential stabilizing control scheme that provides a smooth motion at each step, while considering the robot's kinematic constraints. The robot is able to catch the target at a desired orientation. Extensive simulations demonstrated the efficiency of the proposed method and its success in coping with complex and highly dynamic environments with arbitrary obstacle shapes.

Robust Vision-based Obstacle Avoidance for Micro Aerial Vehicles in Dynamic Environments

Abstract: In this paper, we present an on-board vision-based approach for avoidance of moving obstacles in dynamic environments. Our approach relies on an efficient obstacle detection and tracking algorithm based on depth image pairs, which provides the estimated position, velocity and size of the obstacles. Robust collision avoidance is achieved by formulating a chance-constrained model predictive controller (CC-MPC) to ensure that the collision probability between the micro aerial vehicle (MAV) and each moving obstacle is below a specified threshold. The method takes into account MAV dynamics, state estimation and obstacle sensing uncertainties. The proposed approach is implemented on a quadrotor equipped with a stereo camera and is tested in a variety of environments, showing effective on-line collision avoidance of moving obstacles.