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For robot motion planning there exists a large number of different algorithms, each appropriate for a certain domain, and the right choice of planner depends on the specific use case. The purpose of this paper is to consider the application of bin picking and benchmark a set of motion planning algorithms to identify which are most suited in the given context.

The paper presents a selection of motion planning algorithms and defines benchmarks based on three different bin-picking scenarios. The evaluation is done based on a fixed set of tasks, which are planned and executed on a real and a simulated robot.

The benchmarking shows a clear difference between the planners and generally indicates that algorithms integrating optimization, despite longer planning time, perform better due to a faster execution.

The originality of this work lies in the selected set of planners and the specific choice of application. Most new planners are only compared to existing methods for specific applications chosen to demonstrate the advantages. However, with the specifics of another application, such as bin picking, it is not obvious which planner to choose.

The purpose of this paper is to describe a robot vision system which put rings on hooks that are moving freely on a conveyor belt. The hook can show a significant swinging which can be well approximated by a pendulum movement. The problem is of large relevance for many industrial applications and the challenge is to compute a 3D pose that is sufficiently precise to allow for successful placements of the rings.

This requires a fast and precise tracking and a compensation for latencies connected to the processing of visual information as well as the actual robot action.

The authors achieve this through a precise pose estimation in a high‐resolution stereo setup, as well as a modeling of the hook movement as a combination of a translational and a pendulum movement.

The paper shows that under normal conditions close to 100 percent success can be achieved such that this technology now can be transferred into industrial systems.

The purpose of this paper is to present a dual manipulator system for aloft hot-line assembly tasks of connection fittings in 110-kv intelligent substation, which is significant to the research on hot-line working robots.

This paper addresses the challenges of the task and presents a dual manipulator system which can overcome these challenges to realize the robotic assembly of connection fittings in narrow space without impacting the safe distance of both phase to phase and phase to ground. Two manipulators share a same global reference coordinate. The mission of Manipulator 1 is to position the fixed part of connection fittings and screw the bolts on it. Visual computing provides the approximately position for the end-effector of Manipulator 2, after which The Manipulator 2 carries the removable part of connection fittings to this position. Then, the assembly task could be completed with the posture of the Manipulator 2 adjusted following the guidance by force-position control.

The dual manipulator system can position the target under different illumination conditions and complete fast assembly of connect fittings in 110-kV substation. No strong arc discharge or surface erosion phenomenon has been observed.

This dual manipulator system will be particularly useful for the hot-line assembly of connection fittings in 110-kv intelligent substation, as well as some assembly tasks where uncertain target position and complex contact surface such as cylindrical hole is involved.

This study presents a dual manipulator system used by a field robot working in 110-kv intelligent substation. The system is able to achieve the connection fittings assembly task under energized simulation experimental system. Unlike other peg-in-hole assembly strategy, it does not require high stability of manipulator or plane contact surface around the hole.