Learning Social Affordance Grammar from Videos: Transferring Human Interactions to Human-Robot Interactions

In this paper, we present a general framework for learning social affordance grammar as a spatiotemporal AND-OR graph (ST-AOG) from RGB-D videos of human interactions, and transfer the grammar to humanoids to enable a real-time motion inference for human-robot interaction (HRI). Based on Gibbs sampling, our weakly supervised grammar learning can automatically construct a hierarchical representation of an interaction with long-term joint sub-tasks of both agents and short term atomic actions of individual agents. Based on a new RGB-D video dataset with rich instances of human interactions, our experiments of Baxter simulation, human evaluation, and real Baxter test demonstrate that the model learned from limited training data successfully generates human-like behaviors in unseen scenarios and outperforms both baselines.Comment: The 2017 IEEE International Conference on Robotics and Automation (ICRA

A self-mobile skeleton in the presence of external loads

Multicore clusters provide cost-effective platforms for running CPU-intensive and data-intensive parallel applications. To effectively utilise these platforms, sharing their resources is needed amongst the applications rather than dedicated environments. When such computational platforms are shared, user applications must compete at runtime for the same resource so the demand is irregular and hence the load is changeable and unpredictable. This thesis explores a mechanism to exploit shared multicore clusters taking into account the external load. This mechanism seeks to reduce runtime by finding the best computing locations to serve the running computations. We propose a generic algorithmic data-parallel skeleton which is aware of its computations and the load state of the computing environment. This skeleton is structured using the Master/Worker pattern where the master and workers are distributed on the nodes of the cluster. This skeleton divides the problem into computations where all these computations are initiated by the master and coordinated by the distributed workers. Moreover, the skeleton has built-in mobility to implicitly move the parallel computations between two workers. This mobility is data mobility controlled by the application, the skeleton. This skeleton is not problem-specific and therefore it is able to execute different kinds of problems. Our experiments suggest that this skeleton is able to efficiently compensate for unpredictable load variations. We also propose a performance cost model that estimates the continuation time of the running computations locally and remotely. This model also takes the network delay, data size and the load state as inputs to estimate the transfer time of the potential movement. Our experiments demonstrate that this model takes accurate decisions based on estimates in different load patterns to reduce the total execution time. This model is problem-independent because it considers the progress of all current computations. Moreover, this model is based on measurements so it is not dependent on the programming language. Furthermore, this model takes into account the load state of the nodes on which the computation run. This state includes the characteristics of the nodes and hence this model is architecture-independent. Because the scheduling has direct impact on system performance, we support the skeleton with a cost-informed scheduler that uses a hybrid scheduling policy to improve the dynamicity and adaptivity of the skeleton. This scheduler has agents distributed over the participating workers to keep the load information up to date, trigger the estimations, and facilitate the mobility operations. On runtime, the skeleton co-schedules its computations over computational resources without interfering with the native operating system scheduler. We demonstrate that using a hybrid approach the system makes mobility decisions which lead to improved performance and scalability over large number of computational resources. Our experiments suggest that the adaptivity of our skeleton in shared environment improves the performance and reduces resource contention on nodes that are heavily loaded. Therefore, this adaptivity allows other applications to acquire more resources. Finally, our experiments show that the load scheduler has a low incurred overhead, not exceeding 0.6%, compared to the total execution time

Innovative Technologies for Human Exploration: Opportunities for Partnerships and Leveraging Novel Technologies External to NASA

Human spaceflight organizations have ambitious goals for expanding human presence throughout the solar system. To meet these goals, spaceflight organizations have to overcome complex technical challenges for human missions to Mars, Near Earth Asteroids, and other distant celestial bodies. Resolving these challenges requires considerable resources and technological innovations, such as advancements in human health and countermeasures for space environments; self-sustaining habitats; advanced power and propulsion systems; and information technologies. Today, government space agencies seek cooperative endeavors to reduce cost burdens, improve human exploration capabilities, and foster knowledge sharing among human spaceflight organizations. This paper looks at potential opportunities for partnerships and spin-ins from economic sectors outside the space industry. It highlights innovative technologies and breakthrough concepts that could have significant impacts on space exploration and identifies organizations throughout the broader economy that specialize in these technologies

Innovative Technologies for Global Space Exploration

Under the direction of NASA's Exploration Systems Mission Directorate (ESMD), Directorate Integration Office (DIO), The Tauri Group with NASA's Technology Assessment and Integration Team (TAIT) completed several studies and white papers that identify novel technologies for human exploration. These studies provide technical inputs to space exploration roadmaps, identify potential organizations for exploration partnerships, and detail crosscutting technologies that may meet some of NASA's critical needs. These studies are supported by a relational database of more than 400 externally funded technologies relevant to current exploration challenges. The identified technologies can be integrated into existing and developing roadmaps to leverage external resources, thereby reducing the cost of space exploration. This approach to identifying potential spin-in technologies and partnerships could apply to other national space programs, as well as international and multi-government activities. This paper highlights innovative technologies and potential partnerships from economic sectors that historically are less connected to space exploration. It includes breakthrough concepts that could have a significant impact on space exploration and discusses the role of breakthrough concepts in technology planning. Technologies and partnerships are from NASA's Technology Horizons and Technology Frontiers game-changing and breakthrough technology reports as well as the External Government Technology Dataset, briefly described in the paper. The paper highlights example novel technologies that could be spun-in from government and commercial sources, including virtual worlds, synthetic biology, and human augmentation. It will consider how these technologies can impact space exploration and will discuss ongoing activities for planning and preparing them

Mechanical Description of a Hyper-Redundant Robot Joint Mechanism Used for a Design of a Biomimetic Robotic Fish

A biologically inspired robot in the form of fish (mackerel) model using rubber (as the biomimetic material) for its hyper-redundant joint is presented in this paper. Computerized simulation of the most critical part of the model (the peduncle) shows that the rubber joints will be able to take up the stress that will be created. Furthermore, the frequency-induced softening of the rubber used was found to be critical if the joints are going to oscillate at frequency above 25 Hz. The robotic fish was able to attain a speed of 0.985 m/s while the tail beats at a maximum of 1.7 Hz when tested inside water. Furthermore, a minimum turning radius of 0.8 m (approximately 2 times the fish body length) was achieved

Code management automation for Erlang remote actors

Distributed Erlang provides mechanisms for spawning actors remotely through its remote spawn BIF. However, for remote spawn to function properly, the node hosting the spawned actor must share the same codebase as that of the node launching the actor. This assumption turns out to be too strong for various distributed settings. We propose a higher-level framework for the remote spawn of side effect free actors, abstracting from and automating codebase migration and management.peer-reviewe