We describe a mobile manipulation hardware and software system capable of autonomously performing complex human-level tasks in real homes, after being taught the task with a single demonstration from a person in virtual reality. This is enabled by a highly capable mobile manipulation robot, whole-body task space hybrid position/force control, teaching of parameterized primitives linked to a robust learned dense visual embeddings representation of the scene, and a task graph of the taught behaviors. We demonstrate the robustness of the approach by presenting results for performing a variety of tasks, under different environmental conditions, in multiple real homes. Our approach achieves 85% overall success rate on three tasks that consist of an average of 45 behaviors each. The video is available at: https://youtu.be/HSyAGMGikLk.

There has been an increasing interest in mobile manipulators that are capable of performing physical work in living spaces worldwide, corresponding to an aging population with declining birth rates with the expectation of improving quality of life (QoL). Research and development is a must in intelligent sensing and software which will enable advanced recognition, judgment, and motion to realize household work by robots. In order to accelerate this research, we have developed a compact and safe research platform, Human Support Robot (HSR), which can be operated in an actual home environment. We assume that overall R&D will accelerate by using a common robot platform among many researchers since that enables them to share their research results. Currently, the number of HSR users is expanding to 33 sites in 8 countries worldwide (as of February 15, 2018). Software and technical knowledge of all users is shared through a community website. HSR has been adopted as a standard platform for international robot competitions such as RoboCup@Home and World Robot Summit (WRS). HSR is provided to participants of those competitions through public offering. In this paper, we describe HSR's development background, and technical detail of its hardware and software. Specifically, we describe its omnidirectional mobile base using the dual-wheel caster-drive mechanism, which is the basis of HSR's operational movement and a novel whole body motion control system. Finally, we describe the results of utilization in RoboCup@Home and field tests in order to demonstrate the effect of introducing the platform.

The task of visual relationship recognition (VRR) is recognizing multiple objects and their relationships in an image. A fundamental difficulty of this task is class-number scalability, since the number of possible relationships we need to consider causes combinatorial explosion. Another difficulty of this task is modeling how to avoid outputting semantically redundant relationships. To overcome these challenges, this paper proposes a novel architecture with a recurrent neural network (RNN) and triplet unit (TU). The RNN allows our model to be optimized for outputting a sequence of relationships. By optimizing our model to a semantically diverse relationship sequence, we increase the variety in output relationships. At each step of the RNN, our TU enables the model to classify a relationship while achieving class-number scalability by decomposing a relationship into a subject-predicate-object (SPO) triplet. We evaluate our model on various datasets and compare the results to a baseline. These experimental results show our model's superior recall and precision with fewer predictions compared to the baseline, even as it produces greater variety in relationships.

Slim slime robot (SSR), looks like an active cord mechanism (the snake-like robot) and composes units that can stretch, shrink and bend actively, is for several tasks in narrow spaces such as to move under collapsed houses or for inspection of pipelines in plants. In this paper, we propose the new concept, which is named "bridle drive". We developed the prototype model of the units of the SSR-2.3. Each unit has a bridle bellows composed of a large caliber bellows and wire lock system. The use of bridle bellows allows to produce a high output using air pressure, its shape can be changed by controlling the length of the wires.