Experimental robotics by Oussama Khatib, Oussama Khatib, Vijay Kumar, Daniela Rus

By Oussama Khatib, Oussama Khatib, Vijay Kumar, Daniela Rus

The overseas Symposium on Experimental Robotics (ISER) is a sequence of bi-annual conferences that are geared up in a rotating model round North the United States, Europe and Asia/Oceania. The aim of ISER is to supply a discussion board for study in robotics that makes a speciality of novelty of theoretical contributions proven through experimental effects. The conferences are conceived to assemble, in a small staff surroundings, researchers from all over the world who're within the vanguard of experimental robotics study.

This specific reference provides the most recent advances around the a number of fields of robotics, with principles that aren't merely conceived conceptually but additionally explored experimentally. It collects contributions at the present advancements and new instructions within the box of experimental robotics, that are in line with the papers awarded on the 10th ISER held in Rio de Janeiro, July 2006.

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Motion Planning for Robotic Manipulation of Deformable Linear Objects 25 Vision-based approaches to DLO manipulation have been proposed in [9] and [12]. In our work, we do not rely on the availablity of sensing systems to guide the manipulation in real-time. 1 Geometric Model We describe the geometry of a DLO by a curved cylinder of curvilinear length L and constant circular cross-section of non-zero radius. : c : s ∈ [0, L] → c(s) ∈ R3 , where c(0) is referred to as the tail of the DLO and c(L) as its head.

The joint torque vector τi ∈ R3 for finger i (i = 1, 2) is given by the following simple PID control scheme: τi (t) = kP qei (t) + kI qei (t)dt + kD q˙ei (t) qei (t) = qti (t) − qci (t) (1) (2) where kP , kI , and kD are proportional, integral, and derivative gains, and qei (t) the error of the joint angle between the target joint angle qti (t) and the current joint angle qci (t). Current joint angles qci (t) are acquired by rotary encoder mounted on each motor. To control the grasping force between the two fingers, the thickness of the soft material is controlled by changing the target joint angle qti (t).

Then, using knowledge of the camera position C ∈ R3 and pose, each predicted grasp in the image plane becomes a ray, R = C + tˆ r , with direction rˆ ∈ R3 , ||ˆ r ||2 = 1. Here, t ∈ R+ represents the distance along the ray from the camera. To account for uncertainty in the prediction, we assume a Gaussian error around this ray with variance σ 2 = αt2 , which increases with distance t from the camera, because of image projective transformation. Thus, each ray is represented by a cone centered on the ray with Gaussian spread.

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