The Particle-based Rapidly-exploring Random Tree (pRRT) algorithm is a new method for planetary rover path planning in very rough terrain. The Rapidly-exploring Random Tree algorithm is a planning technique that accounts for effects such as vehicle dynamics by incrementally building a tree of reachable states. pRRT extends the conventional RRT algorithm by explicitly considering uncertainty in ...

Abstract—One of the modern global trends is accelerated formation a “blue economy” based on transport and logistics, resource raw materials, other opportunities seas oceans, which occupy more than 70% Earth’s surface. The article substantiates growth in importance maritime economic activity for Russian Federation emphasizes peculiarities realizing its interests World Ocean, taking into account ...

background: empowerment of people with diabetes means integrating diabetes with identity. however, others’ stigmatization can influence it. although diabetes is so prevalent among iranians, there is little knowledge about diabetes‑related stigma in iran. the present study explored diabetes‑related stigma in people living with type 1 diabetes in isfahan. materials and methods: a conventional con...

Dynamic environments have obstacles that unpredictably appear, disappear, or move. We present the first sampling-based replanning algorithm that is asymptotically optimal and single-query (designed for situation in which a priori offline computation is unavailable). Our algorithm, RRTX, refines and repairs the same search-graph over the entire duration of navigation (in contrast to previous sin...

This paper focuses on the optimal motion planning problem for cooperative aerial manipulation. We use the rapidly exploring random trees star (RRT*) algorithm that finds feasible paths quickly and optimizes them. For local planning within RRT*, we developed a trajectory planner using Bezier-curve which utilizes the differential flatness property of the aerial manipulator. Time-parameterization ...

We present Kinodynamic RRT*, an incremental sampling-based approach for asymptotically optimal motion planning for robots with linear differential constraints. Our approach extends RRT*, which was introduced for holonomic robots [8], by using a fixed-final-statefree-final-time controller that exactly and optimally connects any pair of states, where the cost function is expressed as a trade-off ...

Visual robot navigation within large-scale, semistructured environments deals with various challenges such as computation intensive path planning algorithms or insufficient knowledge about traversable spaces. Moreover, many stateof-the-art navigation approaches only operate locally instead of gaining a more conceptual understanding of the planning objective. This limits the complexity of tasks ...

Avoiding collisions is one of the vital tasks for systems of autonomous mobile agents. We focus on the problem of finding continuous coordinated paths for multiple mobile disc agents in a 2-d environment with polygonal obstacles. The problem is PSPACE-hard, with the state space growing exponentially in the number of agents. Therefore, the state of the art methods include mainly reactive techniq...

Nearest neighbor searching is a fundamental building block of most sampling-based motion planners. We present a novel method for fast exact nearest neighbor searching in SE(3)—the 6 dimensional space that represents rotations and translations in 3 dimensions. SE(3) is commonly used when planning the motions of rigid body robots. Our approach starts by projecting a 4-dimensional cube onto the 3-...