In prior work we established how artificial physics can be used to self-organize swarms of mobile robots into hexagonal formations that move toward a goal. In this paper we extend the framework to moving formations through obstacle fields. We provide important metrics of performance that allow us to (a) compare the utility of different generalized force laws in artificial physics, (b) examine t...

This paper presents the indoor mobile robot that moves automatically without needing environment information beforehand while recognizing the frontal surrounding environment with only one general camera. Based on the frontal image, the robot detects two boundary lines, some obstacle regions, and a moving direction. When the obstacle is detected, the avoidance or stop movement is worked accordin...

In urban environments, the vehicle encounters a wide variety of static and moving obstacles. Obstacles as small as a curb may trip a fast-moving vehicle, so detecting small objects is of great importance. Overhangs and trees may look large obstacles at a distance, but traveling underneath is often possible. Thus, obstacle detection must consider the 3D geometry of the world. Figure 1 depicts a ...

In this paper, a "Moving Window" scheme for detecting lanes and obstacles from the images captured by a CCD camera in an automobile is proposed. Processing the input dynamic images in real time requires high performance hardware as well as efficient software. In order to relieve these requirements for detecting lanes and obstacles from the images in real time, a "Moving Window" scheme is propos...

This letter proposes a new structured method for moving agent to predict the paths of dynamically obstacles and avoid them using risk-aware model predictive control (MPC) scheme. Given noisy measurements priori unknown obstacle trajectory, bootstrapping technique predicts set trajectories. The bootstrapped predictions are incorporated in MPC optimization methodology so as provide probabilistic ...

This paper presents a general description for obstacle avoidance algorithms which can also describe the obstacle avoidance style(walking habit) of moving objects (human beings).A complex sliding mode based obstacle avoidance is presented as a test method, which is learned and modeled by the above mentioned general description. The paper presents simulation results of the sliding mode based navi...

This paper investigates worst-case analysis of a moving obstacle avoidance algorithm for unmanned vehicles in a dynamic environment in the presence of uncertainties and variations. Automatic worst-case search algorithms are developed based on optimization techniques, illustrated by a Pioneer robot with a moving obstacle avoidance algorithm developed using the potential field method. The uncerta...

We have established a novel method of obstacle-avoidance motion planning for mobile robots in dynamic environments, wherein the obstacles are moving with general velocities and accelerations and their motion profiles are not pre-known. A hybrid system is presented in which a global deliberate approach is applied to determine the motion in the desired path line (DPL), and a local reactive approa...

In this paper, we discuss the importance of recognizing and representing both stationary and moving obstacles for the purpose of autonomous driving as well as linking these representation to an ontology of obstacles to aid in deducing additional information about them. With the ability to access additional information about a sensed obstacle, an autonomous vehicle can better forecast where that...