A random sampling scheme for path planning
International Journal of Robotics Research
Robot Motion Planning
Behavior planning for character animation
Proceedings of the 2005 ACM SIGGRAPH/Eurographics symposium on Computer animation
Planning Algorithms
Robust real-time landmark recognition for humanoid robot navigation
ROBIO '09 Proceedings of the 2008 IEEE International Conference on Robotics and Biomimetics
Real-time path planning for humanoid robot navigation
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Vision-Based walking parameter estimation for biped locomotion imitation
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
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Autonomous robot navigation is becoming an increasingly important research topic for mobile robots. In the last few years, significant progress has been made towards stable robotic bipedal walking. This is creating an increased research interest in developing autonomous navigation strategies which are tailored specifically to humanoid robots. Efficient approaches to perception and motion planning, which are suited to the unique characteristics of biped humanoid robots and their typical operating environments, are receiving special interest. In this paper, we present a time-efficient motion planning system for a Fujitsu HOAP-2 humanoid robot. The sampling based algorithm is used to provide the robot with minimal free configuration space which is sampled to extract the robot path. For collision detection, a cylinder model is used to approximate the trajectory for the body center of the humanoid robot during navigation. It calculates the actual distances required to execute different actions of the robot and compares them with the distances to the nearest obstacles. The A* search algorithm is then implemented to find smooth and low-cost footstep placements of the humanoid robot within the resulting configuration space. The proposed hybrid algorithm reduces searching time and produces a smoother path for the humanoid robot at a low cost.