Nothing Special   »   [go: up one dir, main page]

Chen et al., 2015 - Google Patents

An improved path planning method based on artificial potential field for a mobile robot

Chen et al., 2015

View PDF
Document ID
10473363937426826784
Author
Chen W
Wu X
Lu Y
Publication year
Publication venue
Cybernetics and information technologies

External Links

Snippet

To solve the problem of local minima and unreachable destination of the traditional artificial potential field method in mobile robot path planning, chaos optimization is introduced to improve the artificial potential field method. The potential field function was adopted as a …
Continue reading at sciendo.com (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0287—Control of position or course in two dimensions specially adapted to land vehicles involving a plurality of land vehicles, e.g. fleet or convoy travelling
    • G05D1/0291—Fleet control
    • G05D1/0295—Fleet control by at least one leading vehicle of the fleet
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0255—Control of position or course in two dimensions specially adapted to land vehicles using acoustic signals, e.g. ultra-sonic singals

Similar Documents

Publication Publication Date Title
Chen et al. An improved path planning method based on artificial potential field for a mobile robot
Shi et al. A local obstacle avoidance method for mobile robots in partially known environment
CN107168324B (en) Robot path planning method based on ANFIS fuzzy neural network
Chyan et al. Obstacle avoidance control of redundant robots using variants of particle swarm optimization
Liu et al. Obstacle avoidance path planning of space manipulator based on improved artificial potential field method
CN103324196A (en) Multi-robot path planning and coordination collision prevention method based on fuzzy logic
Elmi et al. Multi-objective grasshopper optimization algorithm for robot path planning in static environments
Cai et al. A PSO-based approach with fuzzy obstacle avoidance for cooperative multi-robots in unknown environments
Panigrahi et al. A novel intelligent mobile robot navigation technique for avoiding obstacles using RBF neural network
Cai et al. A potential field-based PSO approach for cooperative target searching of multi-robots
Manzoor et al. A coordinated navigation strategy for multi-robots to capture a target moving with unknown speed
Sekiguchi et al. Human-friendly control system design for two-wheeled service robot with optimal control approach
Palm et al. Particle swarm optimization of potential fields for obstacle avoidance
Shen et al. Multi-robot cooperative hunting
Boujelben et al. A reactive approach for mobile robot navigation in static and dynamic environment using fuzzy logic control
Adderson et al. Formation shaping control for multi-agent systems with obstacle avoidance and dynamic leader selection
Niu et al. The adaptive control based on BP neural network identification for two-wheeled robot
Bi et al. Hierarchical path planning approach for mobile robot navigation under the dynamic environment
Singh et al. Learning safe cooperative policies in autonomous multi-UAV navigation
Ćosić et al. Advanced algorithms for mobile robot motion planning and tracking in structured static environments using particle swarm optimization
Algabri et al. Optimization of fuzzy logic controller using PSO for mobile robot navigation in an unknown environment
Billah et al. The multi-agent group motions generated by models of insect small target detector neurons and feedback
Wang Robot obstacle avoidance and navigation control algorithm research based on multi-sensor information fusion
Cai et al. A PSO-based approach to cooperative foraging multi-robots in unknown environments
Ren et al. Research on Q-ELM algorithm in robot path planning