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In this paper, a novel 3-D motion trajectory signature is introduced to serve as an effective description to the raw trajectory. More importantly, based on the trajectory signature, a probabilistic model-based cluster signature is further developed for modeling a motion class. The cluster signature is a mixture model-based motion description that is useful for motion class perception, recognition...
In this paper, we propose a novel concept of motion descriptor to serve as a fundamental mechanism to describe free form and long-term spatiotemporal motions. The motions are characterized by the underlying motion trajectories extracted via visual tracking. The motion descriptor is a so-called signature description of the motion trajectories. We first present the rationale of the signature definition...
This paper presents a new turning maneuver generation method for a multilink biomimetic robotic fish, in which smooth step functions are introduced to dynamically trigger directed offsets in active and asymmetric swimming. With the proposed method, three basic turning modes can be unified into a general framework by choosing appropriate step-function combinations and dynamic bias. Furthermore, this...
This paper focuses on technical endeavors to develop bio-inspired dolphin-like robots, involving dynamic modeling, mechanical design, as well as motion control. The inspiration and motivation comes from the remarkable swimming abilities of dolphins together with some promising applications in aquatic environments. The thrust in dolphin-like movements in a robotics context can be generated by the up-down-motioned...
Robot learning by demonstration (LbD) has been a natural learning paradigm through which robots can learn the underlying tasks from human's demonstrations. In most LbD related work, the demonstration normally just includes simple and short-term actions like gestures and grasps. Little attention was paid on the demonstration learning of long-term motions. In this paper, we propose to study the motion...
In most reported works about robot learning by demonstration (LbD), the demonstration is normally limited to simple gestures or grasp actions. In this paper, motion trajectory oriented LbD is studied in which free form 3-D motion trajectory is extracted to characterize certain human demonstrations. We propose to build effective description to motion trajectories to be learned by a robot instead of...
This paper addresses the turning issues of a multilink dolphin-like robot with a pair of mechanical flippers. The propulsion and maneuvering of the robot depend on the dorsoventral oscillations of the tail and the flapping movements of the artificial flippers. Taking into account both mechanical structure and functional characteristics of the dolphin-like robot, we present a practical approach to...
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