The problem of deriving navigation strategies for a fleet of autonomous mobile robots moving in formation is considered.
Navigation strategies for multiple autonomous mobile robots moving in formation The system permits high-speed autonomous navigation including obstacle avoidance, waypoing navigation and path planning in both indoor and outdoor environments. The INL Autonomous Navigation System provides instructions for autonomously navigating a robot. Experimental and statistical results of the interface are also shown in this work.ĭOE Office of Scientific and Technical Information (OSTI.GOV) The SLAM algorithm provides the interface with the information concerning the environment disposition and the pose -position and orientation-of the wheelchair within the environment. The turning strategy is performed by a maneuverability algorithm compatible with the kinematics of the wheelchair and by the SLAM (Simultaneous Localization and Mapping) algorithm. The autonomous driving is performed when the user of the wheelchair has to turn (90, 90 or 180 degrees) within the environment. The joystick directs the motion of the vehicle within the environment. The non- autonomous driving of the robotic wheelchair is made by means of a hand-joystick. The interface performs two navigation modus: non- autonomous and autonomous. The visual interface is developed for the navigation in confined spaces such as narrows corridors or corridor-ends. In this work, a visual interface for the assistance of a robotic wheelchair's navigation is presented. The results of this experiment show the applicability of reducing the workforce with robots.Īutonomous assistance navigation for robotic wheelchairs in confined spaces.Ĭheein, Fernando Auat Carelli, Ricardo De la Cruz, Celso Muller, Sandra Bastos Filho, Teodiano F It achieved a series of operations: moving to a destination, recognizing the positions of items on a shelf, picking up an item, placing it on a cart with its hand, and returning to the starting location. We tested this robot in an unknown environment. To achieve these operations, we designed the robot with three functions: an autonomous navigating function that generates a map and a route in an unknown environment, an item position recognizing function, and a grasping function. The operations are locating a requested item, moving to where the item is placed, finding the item on a shelf or table, and picking the item up from the shelf or the table.
We developed an autonomous navigating and grasping robot. The ability to find and grasp target items in an unknown environment is important for working robots. Kudoh, Hiroyuki Fujimoto, Keisuke Nakayama, Yasuichi Despite realistic actuator error, learned spatial abstractions form a model that supports effective travel.ĭevelopment of autonomous grasping and navigating robot This paper reports on autonomous robots that rely on local spatial perception, learning, and commonsense rationales instead. Optimal navigation for a simulated robot relies on a detailed map and explicit path planning, an approach problematic for real-world robots that are subject to noise and error. Spatial abstraction for autonomous robot navigation.Įpstein, Susan L Aroor, Anoop Evanusa, Matthew Sklar, Elizabeth I Parsons, Simon This paper introduces a new type of robot navigation scheme: SLAM, which can build the environment map in a totally strange environment, and at the same time, locate its own position, so as to achieve autonomous navigation function. Take the common household sweeping robot as an example, which could avoid obstacles, clean the ground and automatically find the charging place Another example is AGV tracking car, which can following the route and reach the destination successfully. With the rapid development of robot technology, robots appear more and more in all aspects of life and social production, people also ask more requirements for the robot, one is that robot capable of autonomous navigation, can recognize the road.
Mobile Robot Designed with Autonomous Navigation SystemĪn, Feng Chen, Qiang Zha, Yanfang Tao, Wenyin