2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2016
DOI: 10.1109/iros.2016.7759461
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Modeling and stochastic optimization of complete coverage under uncertainties in multi-robot base placements

Abstract: Uncertainties in base placements of mobile, autonomous industrial robots can cause incomplete coverage in tasks such as grit-blasting and spray painting. Sensing and localization errors can cause such uncertainties in robot base placements. This paper addresses the problem of collaborative complete coverage under uncertainties through appropriate base placements of multiple mobile and autonomous industrial robots while aiming to optimize the performance of the robot team. A mathematical model for complete cove… Show more

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Cited by 11 publications
(4 citation statements)
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“…Before the cleaning process, the robot calculates a set of strategic base positions (e.g. using the approach presented in [29]) from which it will operate on the vehicle and clean all metallic surfaces of the Note that manipulator motion planning with a fixed or mobile base is not the focus of the paper, but rather the focus is on planning the end-effector path for achieving complete coverage amid changes in the environment. However, as future work, it will be interesting to investigate and incorporate constraints related to the industrial robot's motion when following the end-effector path on the surface.…”
Section: Case Study 4: Coverage Of a Complex Object Amid Changes To The Coverage Areamentioning
confidence: 99%
“…Before the cleaning process, the robot calculates a set of strategic base positions (e.g. using the approach presented in [29]) from which it will operate on the vehicle and clean all metallic surfaces of the Note that manipulator motion planning with a fixed or mobile base is not the focus of the paper, but rather the focus is on planning the end-effector path for achieving complete coverage amid changes in the environment. However, as future work, it will be interesting to investigate and incorporate constraints related to the industrial robot's motion when following the end-effector path on the surface.…”
Section: Case Study 4: Coverage Of a Complex Object Amid Changes To The Coverage Areamentioning
confidence: 99%
“…The visiting sequence of the BVs by the I-AUV can be optimized, e.g. using optimization-based approaches [15], [16].…”
Section: A Case Study 1: Marine Growth Removal From a Bridge Pylonmentioning
confidence: 99%
“…. , n; i =í, where o i (τ j , X) ∈ R 3 and o´i(τ j , X) ∈ R 3 return the position of the way-points that the ith and theíth AIRs execute, respectively, at time step τ j . This objective will also help the multi-AIR path planner (Stage 2) to be more effective in finding feasible solutions.…”
Section: Maximal Distance Between Airs' End-effectorsmentioning
confidence: 99%
“…Autonomous Industrial Robots (AIRs) can be used to perform fiber placement. An AIR [3] is an industrial robot with or without a mobile platform, that has self-awareness and environmental awareness, and can effectively communicate with other AIRs to share information on aspects such as robots' state or operation status, the sensed environment, etc. If the AIR is attached to a mobile platform, then its definition is the same as the Autonomous Industrial Mobile Manipulator (AIMM) [4].…”
Section: Introductionmentioning
confidence: 99%