An Approach to Air-to-Surface Mission Planner on 3D Environments for an Unmanned Combat Aerial Vehicle

Recently, interest in mission autonomy related to Unmanned Combat Aerial Vehicles(UCAVs) for performing highly dangerous Air-to-Surface Missions(ASMs) has been increasing. Regarding autonomous mission planners, studies currently being conducted in this field have been mainly focused on creating a path from a macroscopic 2D environment to a dense target area or proposing a route for intercepting a target. For further improvement, this paper treats a mission planning algorithm on an ASM which can plan the path to the target dense area in consideration of threats spread in a 3D terrain environment while planning the shortest path to intercept multiple targets. To do so, ASMs are considered three sequential mission elements: ingress, intercept, and egress. The ingress and egress elements require a terrain flight path to penetrate deep into the enemy territory. Thus, the proposed terrain flight path planner generates a nap-of-the-earth path to avoid detection by enemy radar while avoiding enemy air defense threats. In the intercept element, the shortest intercept path planner based on the Dubins path concept combined with nonlinear programming is developed to minimize exposure time for survivability. Finally, the integrated ASM planner is applied to several mission scenarios and validated by simulations using a rotorcraft model.

Dynamic path planning over CG-Space of 10DOF Rover with static and randomly moving obstacles using RRT* rewiring

Dynamic path planning is a core research content for intelligent robots. This paper presents a CG-Space-based dynamic path planning and obstacle avoidance algorithm for 10 DOF wheeled mobile robot (Rover) traversing over 3D uneven terrains. CG-Space is the locus of the center of gravity location of Rover while moving on a 3D terrain. A CG-Space-based modified RRT* samples a random space tree structure. Dynamic rewiring this tree can handle the randomly moving obstacles and target in real time. Simulations demonstrate that the Rover can obtain the target location in 3D uneven dynamic environments with fixed and randomly moving obstacles.

An Architecture for Collaborative Terrain Sketching with Mobile Devices

3D terrains used in digital animations and videogames are typically created by several collaborators with a single-user application, which constrains them to update the shared terrain from their PCs, using a turn-taking strategy. Moreover, collaborators have to visualize the terrain through 2D views, confusing novice users when conceiving its shape in 3D. In this article, we describe an architecture for collaborative applications, which allow co-located users to sketch a terrain using their mobile devices concurrently. Two interaction modes are supplied: the standard one and an augmented reality-based mode, which helps collaborators understand the 3D terrain shape. Using the painting with brushesparadigm, users can modify the terrain while visualizing its shape evolution through the camera of their devices. Work coordination is promoted by enriching the 3D space with each collaborator’s avatar, which provides awareness information about identity, location, and current action. We implemented a collaborative application from this architecture that was tested by groups of users, who assessed its hedonic and pragmatic qualities in both interaction modes and compared them with the qualities of a similar Web terrain editor. The results showed that the augmented reality mode of our prototype was considered more attractive and usable by the participants.

Rotated Black Hole: A New Heuristic Optimization for Reducing Localization Error of WSN in 3D Terrain

Wireless sensor network (WSN) attracts the attention of more and more researchers, and it is applied in more and more environment. The localization information is one of the most important information in WSN. This paper proposed a novel algorithm called the rotated black hole (RBH) algorithm, which introduces a rotated optimal path and greatly improves the global search ability of the original black hole (BH) algorithm. Then, the novel algorithm is applied in reducing the localization error of WSN in 3D terrain. CEC 2013 test suit is used to verify the performance of the novel algorithm, and the simulation results show that the novel algorithm has better search performance than other famous intelligence computing algorithms. The localization simulation experiment results reveal that the novel algorithm also has an excellent performance in solving practical problems. WSN localization 3D terrain intelligence computing rotated the black hole algorithm.

WSN Deployment Strategy for Real 3D Terrain Coverage Based on Greedy Algorithm with DEM Probability Coverage Model

The key to the study of node deployment in Wireless Sensor Networks (WSN) is to find the appropriate location of the WSN nodes and reduce the cost of network deployment while meeting the monitoring requirements in the covered area. This paper proposes a WSN node deployment algorithm based on real 3D terrain, which provides an effective solution to the surface-covering problem. First of all, actual geographic elevation data is adopted to conduct surface modeling. The model can vividly reflect the real terrain characteristics of the area to be deployed and make the deployment plan more visible and easy to adjust. Secondly, a probabilistic coverage model based on DEM (Digital Elevation Model) data is proposed. Based on the traditional spherical coverage model, the influence of signal attenuation and terrain occlusion on the coverage model is added to make the deployment model closer to reality. Finally, the Greedy algorithm based on grid scanning is used to deploy nodes. Simulation results show that the proposed algorithm can effectively improve the coverage rate, reduce the deployment cost, and reduce the time and space complexity in solving the WSN node deployment problem under the complex 3D land surface model, which verifies the effectiveness of the proposed algorithm.

Seamless 3D Image Mapping and Mosaicing of Valles Marineris on Mars Using Orbital HRSC Stereo and Panchromatic Images

A seamless mosaic has been constructed including a 3D terrain model at 50 m grid-spacing and a corresponding terrain-corrected orthoimage at 12.5 m using a novel approach applied to ESA Mars Express High Resolution Stereo Camera orbital (HRSC) images of Mars. This method consists of blending and harmonising 3D models and normalising reflectance to a global albedo map. Eleven HRSC image sets were processed to Digital Terrain Models (DTM) based on an opensource stereo photogrammetric package called CASP-GO and merged with 71 published DTMs from the HRSC team. In order to achieve high quality and complete DTM coverage, a new method was developed to combine data derived from different stereo matching approaches to achieve a uniform outcome. This new approach was developed for high-accuracy data fusion of different DTMs at dissimilar grid-spacing and provenance which employs joint 3D and image co-registration, and B-spline fitting against the global Mars Orbiter Laser Altimeter (MOLA) standard reference. Each HRSC strip is normalised against a global albedo map to ensure that the very different lighting conditions could be corrected and resulting in a tiled set of seamless mosaics. The final 3D terrain model is compared against the MOLA height reference and the results shown of this intercomparison both in altitude and planum. Visualisation and access mechanisms to the final open access products are described.

Shape-induced obstacle attraction and repulsion during dynamic locomotion

Robots still struggle to dynamically traverse complex 3D terrain with many large obstacles, an ability required for many critical applications. Body–obstacle interaction is often inevitable and induces perturbation and uncertainty in motion that challenges closed-form dynamic modeling. Here, inspired by recent discovery of a terradynamic streamlined shape, we studied how two body shapes interacting with obstacles affect turning and pitching motions of an open-loop multi-legged robot and cockroaches during dynamic locomotion. With a common cuboidal body, the robot was attracted towards obstacles, resulting in pitching up and flipping-over. By contrast, with an elliptical body, the robot was repelled by obstacles and readily traversed. The animal displayed qualitatively similar turning and pitching motions induced by these two body shapes. However, unlike the cuboidal robot, the cuboidal animal was capable of escaping obstacle attraction and subsequent high pitching and flipping over, which inspired us to develop an empirical pitch-and-turn strategy for cuboidal robots. Considering the similarity of our self-propelled body–obstacle interaction with part–feeder interaction in robotic part manipulation, we developed a quasi-static potential energy landscape model to explain the dependence of dynamic locomotion on body shape. Our experimental and modeling results also demonstrated that obstacle attraction or repulsion is an inherent property of locomotor body shape and insensitive to obstacle geometry and size. Our study expands the concept and usefulness of terradynamic shapes for passive control of robot locomotion to traverse large obstacles using physical interaction. Our study is also a step in establishing an energy landscape approach to locomotor transitions.