Small unmanned air vehicles are limited in sensor weight and power such that detection and avoidance of unknown obstacles during flight is difficult. This paper presents a low power low weight method of detection using a laser range finder. In addition, a rapidly-exploring random tree algorithm to generate waypoint paths around obstacles known a priori is presented, and a dynamic geometric algo...

Power transmission involves the crucial part power supply over a country. Continues assessment and inspection can effectively promote the overall productivity of these energy systems. Deployment of mobile robots can provide an effective solution to this problem. In this paper inspection tasks performed by the robot carrying detection instruments and rolling/crawling along the overhead ground wi...

Manual derivation of optimal robot motions for task completion is difficult, especially when a robot is required to balance its actions between opposing preferences. One solution has been to automatically learn near optimal motions with Reinforcement Learning (RL). This has been successful for several tasks including swing-free UAV flight, table tennis, and autonomous driving. However, high-dim...

The goal of this paper is to solve the problem of dynamic obstacle avoidance for a mobile platform using the stochastic optimal control framework to compute paths that are optimal in terms of safety and energy efficiency under constraints. We propose a three-dimensional extension of the Bayesian Occupancy Filter (BOF) (Coué et al. Int. J. Rob. Res. 2006, 25, 19-30) to deal with the noise in the...

We develop a vision system for highly mobile autonomous agents that is capable of dynamic obstacle avoidance. We demonstrate the robust performance of the system in artificial animals with directable, foveated eyes, situated in physics-based virtual worlds. Through active perception, each agent controls its eyes and body by continuously analyzing photorealistic binocular retinal image streams. ...

In robotics applications the speed at which a task may be completed is often limited by computation rather than actuator or sensor through-put. This research concerns the eecient threads-based implementation of motor schema-based reactive navigation for mobile robots. One result of this implementation is the insight that best eeort scheduling ooers sig-niicant performance advantages on uni-and ...

This paper focuses on tracking dynamic targets using a low cost, commercially available drone. The approach presented utilizes a computationally simple potential field controller expanded to operate not only on relative positions, but also relative velocities. A brief background on potential field methods is given, and the design and implementation of the proposed controller is presented. Exper...

The dorsal visual stream codes information crucial to the planning and online control of target-directed reaching movements in dynamic and cluttered environments. Two specific dorsally mediated abilities are the avoidance of obstacles and the online correction for changes in target location. The current study was designed to test whether or not both of these abilities can be performed concurren...

Obstacle avoidance methods approach the problem of mobile robot autonomous navigation by steering the robot in real-time according to the most recent sensor readings, being suitable to dynamic or unknown environments. However, real-time performance is commonly gained by ignoring the robot shape and some or all of its kinematic restrictions which may lead to poor navigation performance in many p...

This paper discusses the importance, the complexity and the challenges of mapping mobile robot’s unknown and dynamic environment, besides the role of sensors and the problems inherited in map building. These issues remain largely an open research problems in developing dynamic navigation systems for mobile robots. The paper presenst the state of the art in map building and localization for mobi...