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Lars-Peter Ellekilde

4 accepted papers

2018

Adapting Parameterized Motions Using Iterative Learning and Online Collision Detection

ICRA 2018poster

Achieving both the flexibility and robustness required to advance the use of robotics in small and medium-sized productions is an essential but difficult task. A fundamental problem is making the robot run blindly without additional sensors while still being robust to uncertainties and variations in…

Cited by 3SourceScholar
2018

Optimisation of Trap Design for Vibratory Bowl Feeders

ICRA 2018poster

Vibratory bowl feeders (VBFs) are a widely used option for industrial part feeding, but their design is still largely manual. A subtask of VBF design is determining an optimal parameter set for the passive devices, called traps, which the VBF uses to ensure correct part orientation. This paper propo…

Cited by 21SourceScholar
2016

Kernel density estimation based self-learning sampling strategy for motion planning of repetitive tasks

IROS 2016poster

This paper introduces a new sampling strategy and shows that superior performance can be obtained for a range of sampling based robotic motion planners, used in scenarios with low task variance, as found in many vision guided pick and place operations. The strategy uses kernel density estimation to…

Cited by 21SourceScholar
2015

Automatic error recovery in robot assembly operations using reverse execution

IROS 2015poster

Robotic assembly tasks are in general difficult to program and require a high degree of precision. As the complexity of the task increases it becomes increasingly unlikely that tasks can always be executed without errors. Preventing errors beyond a certain point is economically infeasible, in partic…

Cited by 59SourceScholar