MACRPO: Multi-agent cooperative recurrent policy optimization.

This work considers the problem of learning cooperative policies in multi-agent settings with partially observable and non-stationary environments without a communication channel. We focus on improving information sharing between agents and propose a new multi-agent actor-critic method called (MACRPO). We propose two novel ways of integrating information across agents and time in MACRPO: First, we use a recurrent layer in the critic's network architecture and propose a new framework to use the proposed meta-trajectory to train the recurrent layer.

Multimodal Representation Learning for Place Recognition Using Deep Hebbian Predictive Coding.

Recognising familiar places is a competence required in many engineering applications that interact with the real world such as robot navigation. Combining information from different sensory sources promotes robustness and accuracy of place recognition. However, mismatch in data registration, dimensionality, and timing between modalities remain challenging problems in multisensory place recognition.

DeFINE: Delayed feedback-based immersive navigation environment for studying goal-directed human navigation.

With the advent of consumer-grade products for presenting an immersive virtual environment (VE), there is a growing interest in utilizing VEs for testing human navigation behavior. However, preparing a VE still requires a high level of technical expertise in computer graphics and virtual reality, posing a significant hurdle to embracing the emerging technology. To address this issue, this paper presents Delayed Feedback-based Immersive Navigation Environment (DeFINE), a framework that allows for easy creation and administration of navigation tasks within customizable VEs via intuitive graphical user interfaces and simple settings files.

Impacts of robot implementation on care personnel and clients in elderly-care institutions.

Background: Digital technologies, including robots, are being increasingly used in elderly care. Their impact on users carries implications for successfully integrating technological innovations into care. This study aims to identify the impacts of care-robot implementation on elderly-care service stakeholders.

A Hidden Semi-Markov Model based approach for rehabilitation exercise assessment.

In this paper, a Hidden Semi-Markov Model (HSMM) based approach is proposed to evaluate and monitor body motion during a rehabilitation training program. The approach extracts clinically relevant motion features from skeleton joint trajectories, acquired by the RGB-D camera, and provides a score for the subject's performance. The approach combines different aspects of rule and template based methods.

Optimal reconstruction of approximate planar surfaces using photometric stereo.

Photometric stereo can be used to obtain a fast and noncontact surface reconstruction of Lambertian surfaces. Despite several published works concerning the uncertainties and optimal light configurations of photometric stereo, no solutions for optimal surface reconstruction from noisy real images have been proposed. In this paper, optimal surface reconstruction methods for approximate planar textured surfaces using photometric stereo are derived, given that the statistics of imaging errors are measurable.

Invariance properties of gabor filter-based features--overview and applications.

For almost three decades the use of features based on Gabor filters has been promoted for their useful properties in image processing. The most important properties are related to invariance to illumination, rotation, scale, and translation. These properties are based on the fact that they are all parameters of Gabor filters themselves.