Titlebook: Robot Intelligence Technology and Applications 7; Results from the 10t Jun Jo,Han-Lim Choi,Bela Stantic Conference proceedings 2023 The Edi

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書目名稱Robot Intelligence Technology and Applications 7年度引用學科排名




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cajole

Nonlinear Autoregressive with?Gaussian Process Regression-Based Path-Following Guidance for?UAV Undebances such as wind. We propose an adaptive guidance algorithm consisting of two parts: a baseline path-following guidance law with optimal error dynamics and a nonlinear autoregressive with Gaussian process regression (GP-NAR). Firstly, a baseline path-following guidance law is constructed by adopt

頌揚本人

CEO-MLCPP: Control-Efficient and?Obstacle-Aware Multi-Layer Coverage Path Planner for?3D ReconstructAV). The proposed method rapidly calculates initial viewpoints considering the ground sampling distance (GSD) by partitioning a structure by height. Then, optimal viewpoints are selected by checking the collision and calculating overlaps and coverage. Next, the newly developed collision-aware Travel

Mechanics

發(fā)怨言

Sampling-Based Path Planning Algorithm Considering Moving Obstacles Based on?RRT* obstacles, we need to also consider moving obstacles in a dynamic environment. In multi-agent systems, these obstacles often have known trajectory that must be avoided. Related works in sampling-based algorithms proposed a re-planning mechanism to consider the moving obstacle. However, those algori

萬神殿

Path Following Algorithm with?Small Error for?Guide Robotonment, and the robot moves along the waypoints. The conventional path-following methods, such as the pure pursuit and the parallelogram, overshoot when the waypoint is not straight. The proposed method has three states depending on the robot’s position, angle, and path for reducing the trajectory d

padding

Ostrich

MDP Formulation for?Multi-UAVs Mission Planning with?Refueling Constraintsation of multi-agent mission planning. Using the MDP formulation can make persistent mission planning with refueling constraints. The state space of MDP formulation consists of agents’ locations and the uncertainty. In order to avoid an enormous computation, refueling constraint is excluded for a st

Ordeal

A*-Based Path Planning for?Legged Robots environmental conditions while making the most of the ability to move between non-adjacent terrains. This paper presents an A*-based path-planning algorithm for legged robots. The heuristic functions in A* is constructed mainly based on preference term for long-distance travel and logarithmic barri

interpose