A Multi-agent Approach for Range Image Segmentation
CEEMAS '07 Proceedings of the 5th international Central and Eastern European conference on Multi-Agent Systems and Applications V
An Agent-Based Approach for Range Image Segmentation
Massively Multi-Agent Technology
Chaotic bee swarm optimization algorithm for path planning of mobile robots
EC'09 Proceedings of the 10th WSEAS international conference on evolutionary computing
A forward / inverse motor controller for cognitive robotics
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I
Dynamical movement primitives: Learning attractor models for motor behaviors
Neural Computation
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This paper proposes a new trajectory generation method that allows full control of transient behavior, namely, time-to-target and velocity profile, based on the artificial potential field approach for a real-time robot motion planning problem. Little attention, in fact, has been paid to the temporal aspects of this class of path planning methods. The ability to control the motion time to the target as well as the velocity profile of the generated trajectories, however, is of great interest in real-life applications. In the paper, we argue that such transient behavior should be taken into account within the framework of the artificial potential field approach.