The recent trend in vision-based multi-object tracking (MOT) is heading towards leveraging the representational power of deep learning to jointly learn to detect and track objects. However, existing methods train only...
详细信息
Control of robots in safety-critical tasks and situations where costly errors may occur is paramount for realizing the vision of pervasive human-robot collaborations. For these cases, the ability to use human cognitio...
详细信息
Communication with a robot using brain activity from a human collaborator could provide a direct and fast feedback loop that is easy and natural for the human, thereby enabling a wide variety of intuitive interaction ...
详细信息
Communication with a robot using brain activity from a human collaborator could provide a direct and fast feedback loop that is easy and natural for the human, thereby enabling a wide variety of intuitive interaction ...
详细信息
Communication with a robot using brain activity from a human collaborator could provide a direct and fast feedback loop that is easy and natural for the human, thereby enabling a wide variety of intuitive interaction tasks. This paper explores the application of EEG-measured error-related potentials (ErrPs) to closed-loop robotic control. ErrP signals are particularly useful for robotics tasks because they are naturally occurring within the brain in response to an unexpected error. We decode ErrP signals from a human operator in real time to control a Rethink robotics Baxter robot during a binary object selection task. We also show that utilizing a secondary interactive error-related potential signal generated during this closed-loop robot task can greatly improve classification performance, suggesting new ways in which robots can acquire human feedback. The design and implementation of the complete system is described, and results are presented for realtime closed-loop and open-loop experiments as well as offline analysis of both primary and secondary ErrP signals. These experiments are performed using general population subjects that have not been trained or screened. This work thereby demonstrates the potential for EEG-based feedback methods to facilitate seamless robotic control, and moves closer towards the goal of real-time intuitive interaction.
We prove that the sum of the squared Euclidean distances from the n rows of an n × d matrix A to any compact set that is spanned by k vectors in ?~d can be approximated up to (l + ε)-factor, for an arbitrary sma...
详细信息
ISBN:
(纸本)9781627484855
We prove that the sum of the squared Euclidean distances from the n rows of an n × d matrix A to any compact set that is spanned by k vectors in ?~d can be approximated up to (l + ε)-factor, for an arbitrary small ε > 0, using the O(k/ε~2)-rank approximation of A and a constant. This implies, for example, that the optimal k-means clustering of the rows of A is (1+ε)-approximated by an optimal k-means clustering of their projection on the O(k/ε~2) first right singular vectors (principle components) of A. A (j, k)-coreset for projective clustering is a small set of points that yields a (1 + e)-approximation to the sum of squared distances from the n rows of A to any set of k affine subspaces, each of dimension at most j. Our embedding yields (O, k)-coresets of size O(k) for handling k-means queries, (j, l)-coresets of size O(j) for PCA queries, and (j, k)-coresets of size (logn)~(O(jk)) for any j,k ≥ 1 and constant ε ∈ (0,1/2). Previous coresets usually have a size which is linearly or even exponentially dependent of d, which makes them useless when d ~ n. Using our coresets with the merge-and-reduce approach, we obtain embarrassingly parallel streaming algorithms for problems such as k-means, PCA and projective clustering. These algorithms use update time per point and memory that is polynomial in log n and only linear in d. For cost functions other than squared Euclidean distances we suggest a simple recursive coreset construction that produces coresets of size k~(1/?O(1)) for k-means and a special class of bregman divergences that is less dependent on the properties of the squared Euclidean distance.
This paper describes a robot in the form of a self-folding sheet that is capable of origami-style autonomous folding. We describe the hardware device we designed and fabricated. The device is a sheet with a box-pleate...
详细信息
This paper describes a robot in the form of a self-folding sheet that is capable of origami-style autonomous folding. We describe the hardware device we designed and fabricated. The device is a sheet with a box-pleated pattern and an integrated electronic substrate and actuators. The sheet is programmed and controlled to achieve different shapes using an idea called sticker programming. We describe the sticker controller and its instantiation. We also describe the algorithms for programming and controlling a given sheet to self-fold into a desired shape. Finally we present experiments with a 4×4 hardware device and an 8×8 hardware device.
暂无评论