Hybrid-Adaptive Switched Control for Robotic Manipulator Interacting with Arbitrary Surface Shapes Under Multi-Sensory Guidance

Abstract

Industrial robots rapidly gained popularity as they can perform tasks quickly, repeatedly and accurately in static environments. However, in modern manufacturing, robots should also be able to safely interact with arbitrary objects and dynamically adapt their behavior to various situations. The large masses and rigid constructions of industrial robots prevent them from easily being re-tasked. In this context, this work proposes an immediate solution to make rigid manipulators compliant and able to efficiently handle object interactions, with only an add-on module (a custom designed instrumented compliant wrist) and an original control framework which can easily be ported to different manipulators. The proposed system utilizes both offline and online trajectory planning to achieve fully automated object interaction and surface following with or without contact where no prior knowledge of the objects is available.

To minimize the complexity of the task, the problem is formulated into four interaction motion modes: free, proximity, contact and a blend of those. The free motion mode guides the robot towards the object of interest using information provided by a RGB-D sensor. The RGB-D sensor is used to collect raw 3D information on the environment and construct an approximate 3D model of an object of interest in the scene. In order to completely explore the object, a novel coverage path planning technique is proposed to generate a primary (offline) trajectory. However, RGB-D sensors provide only limited accuracy on the depth measurements and create blind spot when it reaches close to surfaces. Therefore, the offline trajectory is then further refined by applying the proximity motion mode and contact motion mode or a blend of them (blend motion mode) that allow the robot to dynamically interact with arbitrary objects and adapt to the surfaces it approaches or touches using live proximity and contact feedback from the compliant wrist.

To achieve seamless and efficient integration of the sensory information and smoothly switch between different interaction modes, an original hybrid switching scheme is proposed that applies a supervisory (decision making) module and a mixture of hard and blend switches to support data fusion from multiple sensing sources by combining pairs of the main motion modes. Experimental results using a CRS-F3 manipulator demonstrate the feasibility and performance of the proposed method.