When and Where Will AI Meet Robotics? Issues in Representation

Because perception-action systems are necessarily constrained by the physics of time and space, robotocists often assume they are best described using differential equations, a language that is specialized for describing the evolution of variables that represent physical quantities. However, when it comes to decision making, where the representations involved refer to goals, strategies, and preferences, AI offers a diverse range of formalisms to the modeler. However, the relationship between these two levels of representation -- signal and symbol -- are not well understood. If we are to achieve success in modeling intelligent physical agents, robotics and AI must reach a new consensus on how to integrate perception-action systems with systems designed for abstract reasoning.

[1]  Anthony G. Cohn.  The challenge of qualitative spatial reasoning , 1995, CSUR.

[2]  P. Ramadge,et al.  Supervisory control of a class of discrete event processes , 1987 .

[3]  Jayant Shah,et al.  Extraction of Shape Skeletons from Grayscale Images , 1997, Comput. Vis. Image Underst..

[4]  Ronald C. Arkin,et al.  An Behavior-based Robotics , 1998 .

[5]  Ernst D. Dickmanns,et al.  Vehicles Capable of Dynamic Vision: A New Breed of Technical Beings? , 1998, Artif. Intell..

[6]  Roger W. Brockett,et al.  Hybrid Models for Motion Control Systems , 1993 .

[7]  Gregor Schöner,et al.  Dynamics of behavior: Theory and applications for autonomous robot architectures , 1995, Robotics Auton. Syst..

[8]  Jitendra Malik,et al.  Self Inducing Relational Distance and Its Application to Image Segmentation , 1998, ECCV.

[9]  Jana Kosecka.  A framework for modeling and verifying visually guided agents: design, analysis and experiments , 1996 .

[10]  Devika Subramanian,et al.  Provably Bounded Optimal Agents , 1993, IJCAI.

[11]  Ruzena Bajcsy,et al.  Scaling the Dynamic Approach to Path Planning and Control: Competition among Behavioral Constraints , 1999, Int. J. Robotics Res..

[12]  Rachid Alami,et al.  An Architecture for Autonomy , 1998, Int. J. Robotics Res..

[13]  Eliseo Clementini,et al.  Qualitative Representation of Positional Information , 1997, Artif. Intell..

[14]  Hans-Hellmut Nagel,et al.  Bias-corrected optical flow estimation for road vehicle tracking , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[15]  Erik Sandewall.  Features and fluents : representation of knowledge about dynamical systems , 1994 .