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IJAIT
2008
146views more  IJAIT 2008»
15 years 4 months ago
Learning to Behave in Space: a Qualitative Spatial Representation for Robot Navigation with Reinforcement Learning
ion mechanism to create a representation of space consisting of the circular order of detected landmarks and the relative position of walls towards the agent's moving directio...
Lutz Frommberger
AGENTS
1998
Springer
15 years 8 months ago
Learning Situation-Dependent Costs: Improving Planning from Probabilistic Robot Execution
Physical domains are notoriously hard to model completely and correctly, especially to capture the dynamics of the environment. Moreover, since environments change, it is even mor...
Karen Zita Haigh, Manuela M. Veloso
PODC
2010
ACM
15 years 6 months ago
On the computational power of oblivious robots: forming a series of geometric patterns
We study the computational power of a distributed system consisting of simple autonomous robots moving on the plane. The robots are endowed with visual perception but do not have ...
Shantanu Das, Paola Flocchini, Nicola Santoro, Mas...
AAAI
2006
15 years 5 months ago
The Robot Intelligence Kernel
The Robot Intelligence Kernel (RIK) is a portable, reconfigurable suite of perceptual, behavioral, and cognitive capabilities that can be used across many different platforms, env...
David J. Bruemmer, Douglas A. Few, Miles C. Walton...
ICRA
2010
IEEE
121views Robotics» more  ICRA 2010»
15 years 2 months ago
Real-world validation of three tipover algorithms for mobile robots
— Mobile robot tipover is a concern as it can create dangerous situations for operators and bystanders, cause collateral damage to the surrounding environment, and result in an a...
Philip R. Roan, Aaron Burmeister, Amin Rahimi, Kev...