An approach to robot perception and world modeling that uses a probabilistic tesselated representation of spatial information called the occupancy grid is reviewed. The multidimensional random field maintains stochastic estimates state cells in lattice. To construct sensor-derived map robot's world, cell are obtained by interpreting incoming range readings using sensor models. Bayesian estimation procedures allow incremental updating grid, taken from several sensors over multiple points...

We describe the use of multiple wide-angle sonar range measurements to map surroundings an autonomous mobile robot. A reading provides information concerning empty and occupied volumes in a cone (subtending 30 degrees our case) front sensor. The is modelled as probability profiles projected onto rasterized map, where somewhere everywhere areas are represented. Range from points view (taken sensors on robot, same after robot moves) systematically integrated map. Overlapping re-inforce each...

A sonar-based mapping and navigation system developed for an autonomous mobile robot operating in unknown unstructured environments is described. The uses sonar range data to build a multileveled description of the robot's surroundings. Sonar readings are interpreted using probability profiles determine empty occupied areas. Range measurements from multiple points view integrated into sensor-level map, robust method that combines sensor information such way as cope with uncertainties errors...

In this paper we provide an overview of a new framework for robot perception, real-world modelling, and navigation that uses stochastic tesselated representation spatial information called the Occupancy Grid. The Grid is multi-dimensional random field model maintains probabilistic estimates occupancy state each cell in lattice. Bayesian estimation mechanisms employing sensor models allow incremental updating using multi-view, multi-sensor data, composition multiple maps, decision-making,...

This paper describes a sonar-based mapping and navigation system for autonomous mobile robots operating in unknown unstructured surroundings. The uses sonar range data to build multileveled description of the robot's environment. Sonar maps are represented along several dimensions: Abstraction axis, Geographical Resolution axis. Various kinds problem-solving activities can be performed different levels performance achieved by with these multiple representations maps. major modules Dolphin...

The concept of continuous-time trajectory representation has brought increased accuracy and efficiency to multi-modal sensor fusion in modern SLAM.However, regardless these advantages, its offline property caused by the requirement global batch optimization is critically hindering relevance for real-time life-long applications.In this paper, we present a dense map-centric SLAM method based on cope with problem.The proposed system locally functions similar fashion conventional Continuous-Time...

The authors use occupancy grids to combine range information from sonar and one-dimensional stereo into a two-dimensional map of the vicinity robot. Each cell in contains probabilistic estimate whether it is empty or occupied by an object environment. These estimates are obtained sensor models that describe uncertainty data. A Bayesian estimation scheme applied update current using successive readings each sensor. grid representation simple manipulate, treats different sensors uniformly,...

This paper discusses Project AURORA (autonomous unmanned remote monitoring robotic airship) which focuses on the development of control, navigation, sensing, and inference technologies required for substantially autonomous airships. Our target application areas include use airships environmental, biodiversity, climate research monitoring. Based typical mission requirements, we present arguments that favour over airplanes helicopters as ideal platforms such missions. We outline overall system...

The ability to drive autonomously in heterogeneous environments without GPS, pattern identification (e.g. road following), or artificial landmarks is key field robotics. To address this challenge, we present a complete waypoint navigation framework for unmanned ground vehicles. A Velodyne PUCK VLP-16 LiDAR and an IMU are mounted on autonomous, full size utility vehicle used localization within previously created base map. We redesign six degrees of freedom SLAM algorithm achieve 3D the map,...

In this paper we present the design and control strategies of a novel quadruped climbing robot (named Magneto) with three degrees freedom (3-DOF) actuated limbs 3-DOF compliant magnetic foot. By exploiting its high freedom, Magneto is able to deform body shape squeeze through gaps 23cm, which smaller than standard human entry portholes industrial confined spaces. Its compact foot footprint 4cm allows walk on narrow beams thickness less 5cm, even at varying separation. The inherent...

Legged robots offer the potential of locomotion across various types terrains. Different terrains require different gait patterns to enable greater traversal efficiency. Consequently, as a legged robot transitions from one type terrain another, pattern should be adapted so maximise traction and energy This paper explores use power consumption estimated by in real-time for guiding this transition case statically-stable locomotion. While moving, autonomously assesses its consumption, relates...

Multiple range sensors are essential in mobile robot navigation systems. This introduces the problem of integrating noisy data from multiple and positions into a common description environment. We propose cellular representation called occupancy grid as solution to this problem. In paper, we use grids combine information sonar one-dimensional stereo two-dimensional map vicinity robot. Each cell contains probabilistic estimate whether it is empty or occupied by an object These estimates...

An approach to dynamic planning and control of the perceptual activities an autonomous mobile robot equipped with multiple sensor systems is considered. The conceptually seen as experimenter. author discusses explicit characterization task-specific information requirements, use stochastic models determine utility sensory actions perform selection, application information-theoretic measure extent, accuracy, complexity robot's world model. It shown how loci interest relevant corresponding...