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A survey on active simultaneous localization and map**: State of the art and new frontiers
Active simultaneous localization and map** (SLAM) is the problem of planning and
controlling the motion of a robot to build the most accurate and complete model of the …
controlling the motion of a robot to build the most accurate and complete model of the …
[HTML][HTML] Active map** and robot exploration: A survey
Simultaneous localization and map** responds to the problem of building a map of the
environment without any prior information and based on the data obtained from one or more …
environment without any prior information and based on the data obtained from one or more …
Partially observable markov decision processes in robotics: A survey
Noisy sensing, imperfect control, and environment changes are defining characteristics of
many real-world robot tasks. The partially observable Markov decision process (POMDP) …
many real-world robot tasks. The partially observable Markov decision process (POMDP) …
Learning to explore using active neural slam
DS Chaplot, D Gandhi, S Gupta, A Gupta… - ar**: Toward the robust-perception age
Simultaneous localization and map** (SLAM) consists in the concurrent construction of a
model of the environment (the map), and the estimation of the state of the robot moving …
model of the environment (the map), and the estimation of the state of the robot moving …
Taking the human out of the loop: A review of Bayesian optimization
Big Data applications are typically associated with systems involving large numbers of
users, massive complex software systems, and large-scale heterogeneous computing and …
users, massive complex software systems, and large-scale heterogeneous computing and …
Constrained Bayesian optimization for automatic chemical design using variational autoencoders
Automatic Chemical Design is a framework for generating novel molecules with optimized
properties. The original scheme, featuring Bayesian optimization over the latent space of a …
properties. The original scheme, featuring Bayesian optimization over the latent space of a …
Phoenics: a Bayesian optimizer for chemistry
We report Phoenics, a probabilistic global optimization algorithm identifying the set of
conditions of an experimental or computational procedure which satisfies desired targets …
conditions of an experimental or computational procedure which satisfies desired targets …
Learning exploration policies for navigation
Numerous past works have tackled the problem of task-driven navigation. But, how to
effectively explore a new environment to enable a variety of down-stream tasks has received …
effectively explore a new environment to enable a variety of down-stream tasks has received …
Occupancy anticipation for efficient exploration and navigation
State-of-the-art navigation methods leverage a spatial memory to generalize to new
environments, but their occupancy maps are limited to capturing the geometric structures …
environments, but their occupancy maps are limited to capturing the geometric structures …