Pietro Falco and Ciro Natale
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The paper proposes a method to improve flexibility of the motion planning process for mobile manipulators. The approach is based on the exploitation of perception data available only from simple proximity sensors distributed on the robot. Such data are used to correct pre-planned motions to cope with uncertainties and dynamic changes of the scene at execution time. The algorithm computes robot motion commands aimed at fulfilling the mission by combining two tasks at the same time, i.e. following the planned end-effector path and avoiding obstacles in the environment, by exploiting robot redundancy as well as handling priorities among tasks. Moreover, a technique to smoothly switch between the tasks is presented. To show the effectiveness of the method, four experimental case studies have been presented consisting in a place task executed by a mobile manipulator in an increasingly cluttered scene.
By Matthias Nieuwenhuisen, David Droeschel, Dirk Holz, Jörg Stückler,Alexander Berner, Jun Li, Reinhard Klein, and Sven Behnke
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Grasping individual objects from an unordered pile in a box has been investigated in static scenarios so far. In this paper, we demonstrate bin picking with an anthropomorphic mobile robot. To this end, we extend global navigation techniques by precise local alignment with a transport box. Objects are detected in range images using a shape primitive-based approach. Our approach learns object models from single scans and employs active perception to cope with severe occlusions. Grasps and arm motions are planned in an efficient local multi-resolution height map. All components are integrated and evaluated in a bin picking and part delivery task.
An Autonomous Industrial Mobile Manipulator Concept
By Mads Hvilshøj & Simon Bøgh
This paper presents the concept “autonomous industrial mobile manipulation” (AIMM) based on the mobile manipulator “Little Helper” – an ongoing research project at Aalborg University, Denmark, concerning the development of an autonomous and flexible manufacturing assistant.
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By Advait Jain, Charles C. Kemp
Abstract: Assistive mobile robots that autonomously manipulate objects within everyday settings have the potential to improve the lives of the elderly, injured, and disabled. Within this paper, we present the most recent version of the assistive mobile manipulator EL-E with a focus on the subsystem that enables the robot to retrieve objects from and deliver objects to flat surfaces.
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Abstract: Roboticists are working towards the realization of autonomous mobile manipulators that can perform useful tasks in human environments. These environments pose a significant challenge because of their complexity and inherent uncertainty. They are characterized by having a high dimensional state space. Consequently, performing tasks in these unstructured environments remains a challenge.
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Abstract: Robust robotic manipulation and perception remains a difficult challenge, in particular in unstructured environments. To address this challenge, we propose to couple manipulation and perception. The robot observes its own deliberate interactions with the world.
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Abstract: We introduce a learning-based approach to manip- ulation in unstructured environments. This approach permits au- tonomous acquisition of manipulation expertise from interactions with the environment. The resulting expertise enables a robot to perform effective manipulation based on partial state information.
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By Advait Jain, Charles C. Kemp
Abstract: Previously, we have presented an implementation of impedance control inspired by the Equilibrium Point Hypothesis that we refer to as equilibrium point control (EPC). We have demonstrated that EPC can enable a robot in a fixed position to robustly pull open a variety of doors and drawers, and infer their kinematics without detailed prior models.
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By Siddhartha Srinivasa, David Ferguson, Casey Helfrich, Dmitry Berenson, Alvaro Collet Romea, Rosen Diankov, Garratt Gallagher, Geoffrey Hollinger, James Kuffner, and J Michael Vandeweghe
Abstract:We describe the architecture, algorithms, and experiments with HERB, an autonomous mobile manipulator that performs useful manipulation tasks in the home.
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By Lillian Y. Chang, Siddhartha S. Srinivasa, and Nancy S. Pollard
Published in the Proceedings of th IEEE International Conference on Robotics and Automation (ICRA 2010), May 2010. Finalist for Best Manipulation Paper Award.
Abstract: Studies of human manipulation strategies suggest that pre-grasp object manipulation, such as rotation or sliding of the object to be grasped, can improve task performance by increasing both the task success rate and the quality of load-supporting postures.
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By: Katie Byl
Robot manipulation tasks for a mobile, personal robot will often be importantly distinct from those of a traditional, factory robot arm; correspondingly, appropriate motion planning solutions may be notably different, as well. This paper introduces novel definitions of and solution methods for optimal kinodynamic planning for mobile robot manipulation applications.
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By Heiko Hoffmann, Peter Pastor, Dae-Hyung Park, and Stefan Schaal
IEEE International Conference on Robotics and Automation, 2009
Abstract - Dynamical systems can generate movement trajectories that are robust against perturbations. This article presents an improved modification of the original dynamic movement primitive (DMP) framework by Ijspeert et al.
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By Stephen Hart and Roderic Grupen
In this paper we present a framework for guiding autonomous learning in robot systems. The paradigm we introduce allows a robot to acquire new skills according to an intrinsic motivation function that finds behavioral affordances.
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By G. K. Singh and Jonathan Claassens
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This work addresses the inverse kinematics problem for the 7 Degrees of Freedom Barrett Whole Arm Manipulator with link offsets. The presence of link offsets gives rise to the possibility of the in-elbow & out-elbow poses for a given end-effector pose and is discussed in the paper.
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By Bruno Vilhena Adorno, Philippe Fraisse and Sébastien Druon
Abstract: We propose a set of control strategies for performing two arm manipulation with the goal of simplifying the task definition. In order to develop these strategies we propose a new representation, derived from the cooperative task-space, in the dual quaternion domain.
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By Mads Hvilshøj, Simon Bøgh, Ole Madsen and Morten Kristiansen
At the moment autonomous industrial mobile manipulation (AIMM) is a subject of major focus in development and research environments, as it is a technology with significant potential. However, we are experiencing a lack in calibration techniques, in order to obtain industrially acceptable localization and manipulation tolerances.
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By Bruno Vilhena Adorno, Antônio Padilha Lanari Bó, Philippe Fraisse and Philippe Poignet
Abstract – In this paper we propose a novel approach for interactive manipulation involving a human and a humanoid. The interaction is represented by means of the relative configuration between the human’s and the robot’s hands.
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By Mads Hvilshøj, Simon Bøgh, Oluf Skov Nielsen and Ole Madsen
Purpose – The purpose of this paper is to provide a review of the interdisciplinary research field, autonomous industrial mobile manipulation (AIMM),with an emphasis on physical implementations and applications.
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