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» Constrained Motion Planning in Discrete State Spaces
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ATAL
2009
Springer
15 years 1 months ago
Efficient physics-based planning: sampling search via non-deterministic tactics and skills
Motion planning for mobile agents, such as robots, acting in the physical world is a challenging task, which traditionally concerns safe obstacle avoidance. We are interested in p...
Stefan Zickler, Manuela M. Veloso
ICCV
2001
IEEE
16 years 2 months ago
Capturing Natural Hand Articulation
Vision-based m,otion captu.ring of hand articulation i s - a ch,allengin,g task, since th,e hand presents a m,otion of high, degrees of freedom.. Model-based approach,es could he ...
Ying Wu, John Y. Lin, Thomas S. Huang
AR
2007
105views more  AR 2007»
15 years 12 days ago
Reinforcement learning of a continuous motor sequence with hidden states
—Reinforcement learning is the scheme for unsupervised learning in which robots are expected to acquire behavior skills through self-explorations based on reward signals. There a...
Hiroaki Arie, Tetsuya Ogata, Jun Tani, Shigeki Sug...
ATAL
2010
Springer
15 years 1 months ago
Dynamic generation and execution of human aware navigation plans
d Abstract) Thibault Kruse, Alexandra Kirsch, E. Akin Sisbot, Rachid Alami A robot moving in the presence of humans is highly constrained by the dynamic environment and the need t...
Thibault Kruse, Alexandra Kirsch, Emrah Akin Sisbo...
AIPS
2007
15 years 2 months ago
Learning to Plan Using Harmonic Analysis of Diffusion Models
This paper summarizes research on a new emerging framework for learning to plan using the Markov decision process model (MDP). In this paradigm, two approaches to learning to plan...
Sridhar Mahadevan, Sarah Osentoski, Jeffrey Johns,...