ABSTRACT

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We present a comprehensive approach to handle perception uncertainty to reduce failure rates in robotic bin-picking. Our focus is on mixed-bins. We identify the main failure modes at various stages of the bin-picking task and present methods to recover from them. If uncertainty in part detection leads to perception failure, then human intervention is invoked. Our approach estimates the confidence in the part match provided by an automated perception system, which is used to detect perception failures. Human intervention is also invoked if uncertainty in estimated part location and orientation leads to a singulation planning failure. We have developed a user interface that enables remote human interventions when necessary. Finally, if uncertainty in part posture in the gripper leads to failure in placing the part with the desired accuracy, sensor-less fine-positioning moves are used to correct the final placement errors. We have developed a fine-positioning planner with a suite of fine-motion strategies that offer different tradeoffs between completion time and postural accuracy at the destination. We report our observations from system characterization experiments with a dual-armed Baxter robot, equipped with a Ensenso three-dimensional camera, to perform bin-picking on mixed-bins.

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In this paper, we present the design of RoboCrab, an amphibious robot capable of traversing moderate surf zone environments. By taking inspiration from the morphology, locomotion, and righting behaviors of a horseshoe crab, the robot is designed for traversal and righting on granular terrain, open water, and turbulent surf zones. We present the details of the crab’s morphology that informed the design of our robot. Next, we present the mechanical design, material selection, and manufacturing of the various parts of the robot. We report the results from the computational fluid dynamics simulations used to characterize the robot shell performance. Finally, we present demonstrations of the physical robot walking and righting in a granular environment.

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