How Can Robots Succeed in Unstructured Environments ?

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. Recently, researchers have been successful in developing skills that can handle the complexity of unstructured environments. We hypothesize that those successes are due to a careful implementation that is able to reduce the complexity of the state space, and render the respective problems tractable. In this paper, we analyze this increasing body of literature, in an attempt to extract the common ideas that enable the reduction of the state space. Based on these commonalities, we propose a set of guidelines to facilitate progress for autonomous mobile manipulation in unstructured environments.

[1]  John H. Reif,et al.  Complexity of the mover's problem and generalizations , 1979, 20th Annual Symposium on Foundations of Computer Science (sfcs 1979).

[2]  Alan D. Christiansen,et al.  Learning reliable manipulation strategies without initial physical models , 1990, Proceedings., IEEE International Conference on Robotics and Automation.

[3]  Sebastian Thrun,et al.  The role of exploration in learning control , 1992 .

[4]  D. Sofge.  THE ROLE OF EXPLORATION IN LEARNING CONTROL , 1992 .

[5]  Oliver Brock,et al.  Decomposition-based Motion Planning: Towards Real-time Planning forRobots with Many Degrees of Freedom , 2000 .

[6]  Oliver Brock,et al.  Decomposition-based motion planning: a framework for real-time motion planning in high-dimensional configuration spaces , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[7]  Giorgio Metta,et al.  Grounding vision through experimental manipulation , 2003, Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[8]  Geoffrey L. Barrows,et al.  Flying insect inspired vision for autonomous aerial robot maneuvers in near-earth environments , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[9]  Oliver Brock,et al.  Efficient Motion Planning Based on Disassembly , 2005, Robotics: Science and Systems.

[10]  Alexander Stoytchev,et al.  Behavior-Grounded Representation of Tool Affordances , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[11]  O. Brock,et al.  Viewing Motion Planning as Disassembly : A Decomposition-Based Approach for Non-Stationary Robots , 2005 .

[12]  Shree K. Nayar,et al.  Multiview radial catadioptric imaging for scene capture , 2006, ACM Trans. Graph..

[13]  Oliver Brock,et al.  Elastic Roadmaps: Globally Task-Consistent Motion for Autonomous Mobile Manipulation in Dynamic Environments , 2006, Robotics: Science and Systems.

[14]  Andrea Lockerd Thomaz,et al.  Using perspective taking to learn from ambiguous demonstrations , 2006, Robotics Auton. Syst..

[15]  Steven M. LaValle,et al.  Planning algorithms , 2006 .

[16]  Ashutosh Saxena,et al.  Learning to Grasp Novel Objects Using Vision , 2006, ISER.

[17]  Wei Zhang,et al.  Real-time Accurate Object Detection using Multiple Resolutions , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[18]  Charles C. Kemp,et al.  Human-Robot Interaction for Cooperative Manipulation: Handing Objects to One Another , 2007, RO-MAN 2007 - The 16th IEEE International Symposium on Robot and Human Interactive Communication.

[19]  Robert D. Howe,et al.  Joint Coupling and Actuation Design of Underactuated Hands for Unstructured Environments , 2008 .

[20]  Oliver Brock,et al.  Manipulating articulated objects with interactive perception , 2008, 2008 IEEE International Conference on Robotics and Automation.

[21]  Oliver Brock,et al.  Balancing exploration and exploitation in motion planning , 2008, 2008 IEEE International Conference on Robotics and Automation.

[22]  Erik G. Learned-Miller,et al.  Towards unconstrained face recognition , 2008, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

[23]  Oliver Brock,et al.  Interactive segmentation for manipulation in unstructured environments , 2009, 2009 IEEE International Conference on Robotics and Automation.