Knowledge processing is an essential technique for enabling autonomous robots to do the right thing to the right object in the right way. Using knowledge processing the robots can achieve more flexible and general behavior and better performance. While knowledge representation and reasoning has been a well-established research field in Artificial Intelligence for several decades, little work has been done to design and realize knowledge processing mechanisms for the use in the context of robotic control. In this paper, we report on KNOWROB, a knowledge processing system particularly designed for autonomous personal robots. KNOWROB is a first-order knowledge representation based on description logics that provides specific mechanisms and tools for action-centered representation, for the automated acquisition of grounded concepts through observation and experience, for reasoning about and managing uncertainty, and for fast inference — knowledge processing features that are particularly necessary for autonomous robot control.

/pdf/knowrob-knowledge-processing-for-autonomous-personal-robots-3c1ccjnhdr.pdf

KNOWROB — knowledge processing for autonomous personal robots

Human Behaviour Analysis (HBA) is more and more being of interest for computer vision and artificial intelligence researchers. Its main application areas, like Video Surveillance and Ambient-Assisted Living (AAL), have been in great demand in recent years. This paper provides a review on HBA for AAL and ageing in place purposes focusing specially on vision techniques. First, a clearly defined taxonomy is presented in order to classify the reviewed works, which are consequently presented following a bottom-up abstraction and complexity order. At the motion level, pose and gaze estimation as well as basic human movement recognition are covered. Next, the mainly used action and activity recognition approaches are presented with examples of recent research works. Increasing the degree of semantics and the time interval involved in the HBA, finally the behaviour level is reached. Furthermore, useful tools and datasets are analysed in order to provide help for initiating projects.

https://rua.ua.es/dspace/bitstream/10045/33749/1/2012_Chaaraoui_etal_ESA-pre.pdf

A review on vision techniques applied to Human Behaviour Analysis for Ambient-Assisted Living

Bringing mechanically compliant joints to robots is in the focus of interest world wide, especially in the humanoid robotics community. Variable Stiffness Joints (VSJ) promise to gain a high performing and robust robotic system. The presented DLR Floating Spring Joint (FSJ) is a VSJ module designed for the first 4 axes of the anthropomorphic DLR Hand Arm System. The DLR Hand Arm System aims to match the skills of its natural archetype. For this purpose, the joints have to be extremely compact to fit into the arm. At the same time they require a high power density in order to approximate the human arm skills. The new DLR FSJ is designed completely from an energy based point of view. This addresses not only energy efficient components and low friction design, but also that the potential energy of the spring is used as good as possible. A demonstration of robustness is given by the investigation of a blunt impact to the tip of the arm.

The DLR FSJ: Energy based design of a variable stiffness joint

Service robots will have to accomplish more and more complex, open-ended tasks and regularly acquire new skills. In this work, we propose a new approach to the problem of generating plans for such household robots. Instead composing them from atomic actions — the common approach in robot planning — we propose to transform task descriptions on web sites like ehow.com into executable robot plans. We present methods for automatically converting the instructions from natural language into a formal, logic-based representation, for resolving the word senses using the WordNet database and the Cyc ontology, and for exporting the generated plans into the mobile robot's plan language RPL. We discuss the problem of inferring information that is missing in these descriptions and the problem of grounding the abstract task descriptions in the perception and action system, and we propose techniques for solving them. The whole system works autonomously without human interaction. It has successfully been tested with a set of about 150 natural language directives, of which up to 80% could be correctly transformed.

/pdf/understanding-and-executing-instructions-for-everyday-3a19f8rmrd.pdf

Understanding and executing instructions for everyday manipulation tasks from the World Wide Web

In this paper, we consider the problem of tracking human motion with a 22-DOF kinematic model from depth images. In contrast to existing approaches, our system naturally scales to multiple sensors. The motivation behind our approach, termed Multiple Depth Camera Approach (MDCA), is that by using several cameras, we can significantly improve the tracking quality and reduce ambiguities as for example caused by occlusions. By fusing the depth images of all available cameras into one joint point cloud, we can seamlessly incorporate the available information from multiple sensors into the pose estimation. To track the high-dimensional human pose, we employ state-of-the-art annealed particle filtering and partition sampling. We compute the particle likelihood based on the truncated signed distance of each observed point to a parameterized human shape model. We apply a coarse-to-fine scheme to recognize a wide range of poses to initialize the tracker. In our experiments, we demonstrate that our approach can accurately track human motion in real-time (15Hz) on a GPGPU. In direct comparison to two existing trackers (OpenNI, Microsoft Kinect SDK), we found that our approach is significantly more robust for unconstrained motions and under (partial) occlusions.

https://vision.in.tum.de/_media/spezial/bib/zhang12iros.pdf

Real-time human motion tracking using multiple depth cameras

In this paper we present our work on markerless model-based 3D human motion capture using multiple cameras. We use an industry proven anthropometric human model that was modeled taking ergonomic considerations into account. The outer surface consists of a precise yet compact 3D surface mesh that is mostly rigid on body part level apart from some small but important torsion deformations. Benefits are the ability to capture a great amount of possible human appearances with high accuracy while still having a simple to use and computationally efficient model. We have introduced special optimizations such as caching into the model to improve its performance in tracking applications. Available force and comfort measures within the model provide further opportunities for future research.

3D articulated pose estimation is performed in a Bayesian framework, using a set of hierarchically coupled local particle filters for tracking. This makes it possible to sample efficiently from the high dimensional space of articulated human poses without constraining the allowed movements. Sequences of tracked upper-body as well as full-body motions captured by three cameras show promising results. Despite the high dimensionality of our model (51 DOF) we succeed at tracking using only silhouette overlap as weighting function due to the precise outer appearance of our model and the hierarchical decomposition.

Accurate Human Motion Capture Using an Ergonomics-Based Anthropometric Human Model

Strength prediction for arbitrary postures presupposes correlations between joint angles and joint torques due to the length -- tension relationship of muscles. This paper investigates isometric elbow flexion and extension joint torque curves as a function of elbow flexion, shoulder flexion, and forearm rotation. Numerous authors have already examined elbow joint torque functions. However either only young or male subjects or old subjects with a high sample size but only one measurement posture were used. Alongside posture effects this study focuses on age and gender effects. Therefore four subject groups consisting of five young males, five young females, four old males, and three old females took part. Significant influences were obtained for elbow and shoulder flexion, age and gender. The results show that increasing shoulder flexion leads to decreasing elbow flexion joint torques whereas this effect gains in importance with increasing elbow flexion angles. Unlike previous studies no consistent results were found concerning the influence of forearm rotation. The extension torques were 79 Isometric elbow flexion and extension joint torque measurements considering biomechanical aspects (PDF Download Available). Available from: https://www.researchgate.net/publication/228535401_Isometric_elbow_flexion_and_extension_joint_torque_measurements_considering_biomechanical_aspects [accessed Mar 24, 2016].

Isometric elbow flexion and extension joint torque measurements considering biomechanical aspects

The purpose of this experiment is to obtain isometric knee extension and flexion joint torque - joint angle functions considering necessary biomechanical aspects. In order to examine gender and age effects four different subject groups (10 young males and females, 8 old males and females) were used. Age and gender had a significant influence for both force directions. Not only different maximum values but also different curve shapes were identified for different age groups. Additionally the hip flexion angle significantly influenced the joint torque production.

/pdf/joint-torque-modeling-of-knee-extension-and-flexion-xhj205ksuf.pdf

Joint torque modeling of knee extension and flexion

This pilot study presents an approach to generate percentile values for joint torque characteristics of digital human models. Detailed angle specific joint torque measurements of few subjects are set in relation to extensive measurements of external maximum forces including percentile values based on many subjects by using muti-body simulation. Results indicate the applicability of the approach but do not generate results of high validity due to some sources of errors along the process. More experiments solving these issues and generating valid results are being planned.

/pdf/generation-of-percentile-values-for-human-joint-torque-e23ardzpji.pdf

Generation of Percentile Values for Human Joint Torque Characteristics

A realistic simulation of joint range of motion is critical to a successful application of digital human models. However, current models lack the simulation of inter-joint dependencies. Numerous authors investigated joint range of motion regarding effects of age and gender and extensive data are available, but very few studies took inter-joint dependencies into account. This study aims to fill this gap by measuring active joint range of motion for hip, knee and ankle of 18 subjects using motion capture methods. Joint angles and degrees of freedom of adjacent joints are studied. Results show that there is a strong relation between hip and knee flexion angle for both flexion and extension and mathematical models are given. Other relations were found to be negligible. The results can be of direct use for the application of digital human models.

Lower Limb Joint Range of Motion Considering Inter-joint Dependencies

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