Motion Planning Algorithm of a Multi-Joint Snake-Like Robot Based on Improved Serpenoid Curve
نویسندگان
چکیده
منابع مشابه
Multiple-objective Optimization of Serpentine Locomotion with Snake Robot by Using the NSGA
This paper starts with developing kinematic and dynamic model of a snake shape robot in serpentine locomotion and finishes with actual experimentation. At the beginning the symmetrical and unsymmetrical serpenoid curves are introduced. Kinematics and dynamics of a snake robot on flat and inclined surfaces are obtained for a general n-link robot. SimMechanics toolbox of MATLAB software is employ...
متن کاملMulti-Robot Motion Planning
We present a simple and natural extension of the multi-robot motion planning problem where the robots are partitioned into groups (colors), such that in each group the robots are interchangeable. Every robot is no longer required to move to a specific target, but rather to some target placement that is assigned to its group. We call this problem k-color multi-robot motion planning and provide a...
متن کاملSampling-based Multi-robot Motion Planning
This paper describes a sampling-based approach to multi-robot motion planning. The proposed approach is centralized, which aims to reduce interference between mobile robots such as collision, congestion and deadlock, by increasing the number of waypoints. The implementation based on occupancy grid map is decomposed into three steps: the first step is to identify primary waypoints by using the V...
متن کاملRobot Path Planning Method Based on Improved Genetic Algorithm
This paper presents an improved genetic algorithm for mobile robot path planning. The algorithm uses artificial potential method to establish the initial population, and increases value weights in the fitness function, which increases the controllability of robot path length and path smoothness. In the new algorithm, a flip mutation operator is added, which ensures the individual population col...
متن کاملMobile Robot Path Planning Based on Improved Q Learning Algorithm
For path planning of mobile robot, the traditional Q learning algorithm easy to fall into local optimum, slow convergence etc. issues, this paper proposes a new greedy strategy, multi-target searching of Q learning algorithm. Don't need to create the environment model, the mobile robot from a single-target searching transform into multitarget searching an unknown environment, firstly, by the dy...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Access
سال: 2020
ISSN: 2169-3536
DOI: 10.1109/access.2020.2964486