Sensor-based navigation in cluttered environments
نویسندگان
چکیده
AbstmctIn this paper, we present a new approach to sensor-based navigation in cluttered environments. In our system, tasks are specified in terms of visual goals, and obstacles are detected by a laser range finder. To effect task performance, we introduce a new gain scheduling visual servo controller. Our approach uses a diagonal gain matrix whose entries are adjusted during execution according to one of several proposed gain schedules. Obstacle avoidance is achieved by allowing the detected obstacles to generate artificial repulsive potential fields, which alter the motion of the mobile robot base. Since this motion affects the visionbased control, it is compensated by corresponding camera motions. Finally, we combine the obstacle avoiding and visual servo components of the system so that visual servo tasks can be performed as obstacles are avoided. We illustrate our approach with both simulations and real experiments using our experimental platform HihreZ is . KeywordsSensor-based mobile robotics, visual servoing
منابع مشابه
A Hierarchical SLAM/GPS/INS Sensor Fusion with WLFP for Flying Robo-SAR's Navigation
In this paper, we present the results of a hierarchical SLAM/GPS/INS/WLFP sensor fusion to be used in navigation system devices. Due to low quality of the inertial sensors, even a short-term GPS failure can lower the integrated navigation performance significantly. In addition, in GPS denied environments, most navigation systems need a separate assisting resource, in order to increase the avail...
متن کاملRobot navigation in very cluttered environments by preference-based fuzzy behaviors
One of the key challenges in application of Autonomous Ground Vehicles (AGVs) is navigation in environments that are densely cluttered with obstacles. The control task becomes more complex when the configuration of obstacles is not known a priori. The most popular control methods for such systems are based on reactive local navigation schemes that tightly couple the robot actions to the sensor ...
متن کاملA CBR based pure reactive layer for autonomous robot navigation
This paper presents a new reactive layer using Case-Based Reasoning (CBR) for a hybrid navigation architecture already including a deliberative layer that performs all global planning. Thus, the reactive layer only relies on immediate information about sensors readings, robot heading and relative position to the goal. The proposed layer allows efficient navigation in cluttered environments with...
متن کاملTowards Real-Time Sensor-Based Path Planning in Highly Dynamic Environments
This paper presents work on sensor-based motion planning in initially unknown dynamic environments. Motion detection and probabilistic motion modeling are combined with a smooth navigation function to perform on-line path planning and replanning in cluttered dynamic environments such as public exhibitions. The SLIP algorithm, an extension of Iterative Closest Point, combines motion detection fr...
متن کاملObstacle Avoidance in Cluttered Environments using Optic Flow
Autonomous navigation of a flying vehicle in a cluttered environment has been simulated to demonstrate novel yet simple techniques for avoiding obstacles using optic flow and image loom signals whilst successfully navigating a vehicle towards a goal. The simulation makes use of simulated flow fields calculated on cameras looking downwards, forwards, rearwards and sidewards. This computation cou...
متن کاملMINOS: Multimodal Indoor Simulator for Navigation in Complex Environments
We present MINOS, a simulator designed to support the development of multisensory models for goal-directed navigation in complex indoor environments. The simulator leverages large datasets of complex 3D environments and supports flexible configuration of multimodal sensor suites. We use MINOS to benchmark deep-learning-based navigation methods, to analyze the influence of environmental complexi...
متن کامل