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We propose a real-time depth edge based RGB-D SLAM system for dynamic environment. Our visual odometry method is based on frame-to-keyframe registration, where only depth edge points are used. To reduce the influence of dynamic objects, we propose a static weighting method for edge points in the keyframe. Static weight indicates the likelihood of one point being part of the static environment. This...
In this paper, an adaptive control approach is proposed for performance of constrained robot end-effector movements in presence of uncertainty. In real-world scenarios, complex physical phenomena occuring at the place of interaction may introduce nonlinearities in the system dynamics, which have to be taken into account for proper system control. We currently propose an Extremum Seeking (ES) Model...
Performance of constrained movements in multiple directions of a workspace simultaneously and in presence of uncertainty is a great challenge for robots. Achieving such tasks by employing control policies which are fully determined a priori and do not take into account the system uncertainty can cause undesired stress on the robot end-effector or the environment and result in poor performance. Instead,...
This paper presents an online methodology for imitating human walking motion of a humanoid robot in task and joint space simultaneously. Two aspects are essential for a successful walking imitation: stable footprints represented in task space and motion similarity represented in joint space. The human footprints are recognized from the captured motion data and imitated by the robot through conventional...
This paper explores learning of interaction force skills by human demonstration in dynamic interaction tasks. Skillful force regulation is required in many cases to achieve the goal of a task and at the same time, not to cause undesired stress on the manipulator or the object under manipulation which could result in physical failure. For example, manipulation of compliant objects with varying physical...
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