Depth-based localization for robotic peg-in-tube assembly

Udai, Arun Dayal; Joshi, Ravi Prakash; Saha, Subir Kumar

doi:10.1109/iros.2015.7353871

Cited by 8 publications

(3 citation statements)

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“…gets changed. Another intelligent strategy is described in Chhatpar and Branicky (2001) known as precession-based search which was extended by Udai et al (2015) for a Peg-In-Tube assembly. Again, the tilt of peg and the peg’s center should be known to perform precession.…”

Section: Introductionmentioning

confidence: 99%

“…The force and moment values are very noisy and are not as repeatable as the position values. Therefore, it is better to have a search strategy guided by the position values rather than the force/moment values as discussed by Udai et al (2015). Chhatpar and Branicky (2003), and Chhatpar and Branicky (2005) also describe some general search strategies using analytical maps of peg and hole contact states.…”

Section: Introductionmentioning

confidence: 99%

“…This paper also presents a method to qualitatively simulate the depth profile for a cylindrical peg-in-hole assembly. The existing intelligent search techniques as in Chhatpar and Branicky (2001), Newman et al (2001), Chhatpar and Branicky (2003), Chhatpar and Branicky (2005), Kim et al (2012) and Udai et al (2015) require knowledge of one or the other parameter of the assembly setup, whereas the techniques presented in this paper and Sharma et al (2013) perform the search without the knowledge about assembly parameters like peg orientation, location of peg center, clearance value, etc. Such techniques make the hole search more practical and general-purpose.…”

Section: Introductionmentioning

confidence: 99%

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Peg-In-Hole search using convex optimization techniques

Sharma

Shirwalkar

Pal

2017

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Purpose This paper aims to provide a solution to the first phase of a force-controlled circular Peg-In-Hole assembly using an industrial robot. The paper suggests motion planning of the robot’s end-effector so as to perform Peg-In-Hole search with minimum a priori information of the working environment. Design/methodology/approach The paper models Peg-In-Hole search problem as a problem of finding the minima in depth profile for a particular assembly. Thereafter, various optimization techniques are used to guide the robot to locate minima and complete the hole search. This approach is inspired by a human’s approach of searching a hole by moving peg in various directions so as to search a point of maximum insertion which is same as the minima in depth profile. Findings The usage of optimization techniques for hole search allows the robot to work with minimum a priori information of the working environment. Also, the iterative nature of the techniques adapts to any disturbance during assembly. Practical implications The techniques discussed here are quite useful if a force-controlled assembly needs to be performed in a highly unknown environment and also when the assembly setup can get disturbed in between. Originality/value The concept is original and provides a non-conventional use of optimization techniques, not for optimization of some process directly but for an industrial robot’s motion planning.

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Section: Introductionmentioning

confidence: 99%