Autonomous Mission with a Mobile Manipulator—A Solution to the MBZIRC

Abstract

This work presents the system and approach we employed to tackle the second challenge of the Mohamed Bin Zayed International Robotics Challenge (MBZIRC) 1 . The goal of this challenge is to find a tool panel on a field, pick an appropriate wrench from the panel, and operate a valve stem therewith. For this purpose we use a task-oriented field robot, based on Clearpath Husky with a customized series elastic arm, that can be deployed for versatile purposes. However, to be competitive in a robotic challenge, further specialization and improvements are necessary to achieve a certain task faster and more reliably. A high emphasis is put on designing a system that can operate fully autonomously and independently respond if a subtask was not executed successfully. Moreover, the operator can easily monitor the system through a graphical user interface and, if desired, interact with the robot. We present our algorithms to explore the field, detect the panel, and navigate to it. Furthermore, we use a support vector machine based object detection method to locate the valve stem and wrenches on the panel for visual servoing. Finally, we show the advantages of a force controllable manipulator to handle the valve stem with a tool. This system demonstrated its applicability when fulfilling the entire task fully autonomously during both trials of the Grand Challenge of the MBZIRC 2017.

Deployment of an autonomous mobile manipulator at MBZIRC

“…The second challenge of MBZIRC was exclusively solved by wheeled mobile robots in combination with a manipulator arm. Some teams of the MBZIRC have officially documented their results for challenge 2, for example (Carius, Wermelinger, Rajasekaran, Holtmann, & Hutter, ; Chen et al, ; Engemann, Wiesen, Kallweit, Deshpande, & Schleupen, ; Gandin, ; Shaqura & Shamma, ). Furthermore, team websites provide additional information on the robotic systems used during the competition and most teams have published progress videos.…”

Towards Shared Autonomy Applications using Whole-body Control Formulations of Locomanipulation

“…However, due to the complexity of planning locomanipulation in real-time, locomotion/navigation and manipulation are often treated as separate problems and joined and coordinated by a high-level state machine [2], sequence planner, or shared autonomy control interface [3], [4]. In this case, the problems of optimal base placement [5], navigation to the base placement, and fixed-base manipulation [6], [7] are treated separately, limiting the applicability to static targets and obstacles and disregarding the inherent redundancy of high degree of freedom (DoF) systems.…”

“…In this work, we heavily rely on the whole-body control and perception systems. a mobile platform moving on a surface is often defined as x base ∈ SE (2). This space has the topology of the Special Euclidean group and it is unbounded, i.e., it has no translation and rotation limits.…”

“…Random sampling-based planners, however, are not suited to satisfy general constraints. 2 As thus, we use constraint relaxation as well as a framework to solve constrained time-configuration space problems by decomposition [12] for initialization. We formulate both the real-time control optimization as well as the nonlinear locomanipulation problem in the open source Extensible Optimization Toolset EXOTica [22].…”