Remote Life Support Robot Interface System for Global Task Planning and Local Action Expansion Using Foundation Models

Robot systems capable of executing tasks based on language instructions have been actively researched. It is challenging to convey uncertain information that can only be determined on-site with a single language instruction to the robot. In this study, we propose a system that includes ambiguous parts as template variables in language instructions to communicate the information to be collected and the options to be presented to the robot for predictable uncertain events. This study implements prompt generation for each robot action function based on template variables to collect information, and a feedback system for presenting and selecting options based on template variables for user-to-robot communication. The effectiveness of the proposed system was demonstrated through its application to real-life support tasks performed by the robot.

Vlimb: A Wire-Driven Wearable Robot for Bodily Extension, Balancing Powerfulness and Reachability

Numerous wearable robots have been developed to meet the demands of physical assistance and entertainment. These wearable robots range from body-enhancing types that assist human arms and legs to body-extending types that have extra arms. This study focuses specifically on wearable robots of the latter category, aimed at bodily extension. However, they have not yet achieved the level of powerfulness and reachability equivalent to that of human limbs, limiting their application to entertainment and manipulation tasks involving lightweight objects. Therefore, in this study, we develop an body-extending wearable robot, Vlimb, which has enough powerfulness to lift a human and can perform manipulation. Leveraging the advantages of tendon-driven mechanisms, Vlimb incorporates a wire routing mechanism capable of accommodating both delicate manipulations and robust lifting tasks. Moreover, by introducing a passive ring structure to overcome the limited reachability inherent in tendon-driven mechanisms, Vlimb achieves both the powerfulness and reachability comparable to that of humans. This paper outlines the design methodology of Vlimb, conducts preliminary manipulation and lifting tasks, and verifies its effectiveness.

Integrative Wrapping System for a Dual-Arm Humanoid Robot

Flexible object manipulation of paper and cloth is a major research challenge in robot manipulation. Although there have been efforts to develop hardware that enables specific actions and to realize a single action of paper folding using sim-to-real and learning, there have been few proposals for humanoid robots and systems that enable continuous, multi-step actions of flexible materials. Wrapping an object with paper and tape is more complex and diverse than traditional manipulation research due to the increased number of objects that need to be handled, as well as the three-dimensionality of the operation. In this research, necessary information is organized and coded based on the characteristics of each object handled in wrapping. We also generalize the hardware configuration, manipulation method, and recognition system that enable humanoid wrapping operations. The system will include manipulation with admittance control focusing on paper tension and state evaluation using point clouds to handle three-dimensional flexible objects. Finally, wrapping objects with different shapes is experimented with to show the generality and effectiveness of the proposed system.

Fundamental Three-Dimensional Configuration of Wire-Wound Muscle-Tendon Complex Drive

For robots to become more versatile and expand their areas of application, their bodies need to be suitable for contact with the environment. When the human body comes into contact with the environment, it is possible for it to continue to move even if the positional relationship between muscles or the shape of the muscles changes. We have already focused on the effect of geometric deformation of muscles and proposed a drive system called wire-wound Muscle-Tendon Complex (ww-MTC), an extension of the wire drive system. Our previous study using a robot with a two-dimensional configuration demonstrated several advantages: reduced wire loosening, interference, and wear; improved robustness during environmental contact; and a muscular appearance. However, this design had some problems, such as excessive muscle expansion that hindered inter-muscle movement, and confinement to planar motion. In this study, we develop the ww-MTC into a three-dimensional shape. We present a fundamental construction method for a muscle exterior that expands gently and can be contacted over its entire surface. We also apply the three-dimensional ww-MTC to a 2-axis 3-muscle robot, and confirm that the robot can continue to move while adapting to its environment.

CubiXMusashi: Fusion of Wire-Driven CubiX and Musculoskeletal Humanoid Musashi toward Unlimited Performance

Humanoids exhibit a wide variety in terms of joint configuration, actuators, and degrees of freedom, resulting in different achievable movements and tasks for each type. Particularly, musculoskeletal humanoids are developed to closely emulate human body structure and movement functions, consisting of a skeletal framework driven by numerous muscle actuators. The redundant arrangement of muscles relative to the skeletal degrees of freedom has been used to represent the flexible and complex body movements observed in humans. However, due to this flexible body and high degrees of freedom, modeling, simulation, and control become extremely challenging, limiting the feasible movements and tasks. In this study, we integrate the musculoskeletal humanoid Musashi with the wire-driven robot CubiX, capable of connecting to the environment, to form CubiXMusashi. This combination addresses the shortcomings of traditional musculoskeletal humanoids and enables movements beyond the capabilities of other humanoids. CubiXMusashi connects to the environment with wires and drives by winding them, successfully achieving movements such as pull-up, rising from a lying pose, and mid-air kicking, which are difficult for Musashi alone. This concept demonstrates that various humanoids, not limited to musculoskeletal humanoids, can mitigate their physical constraints and acquire new abilities by connecting to the environment and driving through wires.

Robotic State Recognition with Image-to-Text Retrieval Task of Pre-Trained Vision-Language Model and Black-Box Optimization

State recognition of the environment and objects, such as the open/closed state of doors and the on/off of lights, is indispensable for robots that perform daily life support and security tasks. Until now, state recognition methods have been based on training neural networks from manual annotations, preparing special sensors for the recognition, or manually programming to extract features from point clouds or raw images. In contrast, we propose a robotic state recognition method using a pre-trained vision-language model, which is capable of Image-to-Text Retrieval (ITR) tasks. We prepare several kinds of language prompts in advance, calculate the similarity between these prompts and the current image by ITR, and perform state recognition. By applying the optimal weighting to each prompt using black-box optimization, state recognition can be performed with higher accuracy. Experiments show that this theory enables a variety of state recognitions by simply preparing multiple prompts without retraining neural networks or manual programming. In addition, since only prompts and their weights need to be prepared for each recognizer, there is no need to prepare multiple models, which facilitates resource management. It is possible to recognize the open/closed state of transparent doors, the state of whether water is running or not from a faucet, and even the qualitative state of whether a kitchen is clean or not, which have been challenging so far, through language.

Component Modularized Design of Musculoskeletal Humanoid Platform Musashi to Investigate Learning Control Systems

To develop Musashi as a musculoskeletal humanoid platform to investigate learning control systems, we aimed for a body with flexible musculoskeletal structure, redundant sensors, and easily reconfigurable structure. For this purpose, we develop joint modules that can directly measure joint angles, muscle modules that can realize various muscle routes, and nonlinear elastic units with soft structures, etc. Next, we develop MusashiLarm, a musculoskeletal platform composed of only joint modules, muscle modules, generic bone frames, muscle wire units, and a few attachments. Finally, we develop Musashi, a musculoskeletal humanoid platform which extends MusashiLarm to the whole body design, and conduct several basic experiments and learning control experiments to verify the effectiveness of its concept.

A Robot Kinematics Model Estimation Using Inertial Sensors for On-Site Building Robotics

In order to make robots more useful in a variety of environments, they need to be highly portable so that they can be transported to wherever they are needed, and highly storable so that they can be stored when not in use. We propose "on-site robotics", which uses parts procured at the location where the robot will be active, and propose a new solution to the problem of portability and storability. In this paper, as a proof of concept for on-site robotics, we describe a method for estimating the kinematic model of a robot by using inertial measurement units (IMU) sensor module on rigid links, estimating the relative orientation between modules from angular velocity, and estimating the relative position from the measurement of centrifugal force. At the end of this paper, as an evaluation for this method, we present an experiment in which a robot made up of wooden sticks reaches a target position. In this experiment, even if the combination of the links is changed, the robot is able to reach the target position again immediately after estimation, showing that it can operate even after being reassembled. Our implementation is available on https://github.com/hiroya1224/urdf_estimation_with_imus .

Patterned Structure Muscle : Arbitrary Shaped Wire-driven Artificial Muscle Utilizing Anisotropic Flexible Structure for Musculoskeletal Robots

Muscles of the human body are composed of tiny actuators made up of myosin and actin filaments. They can exert force in various shapes such as curved or flat, under contact forces and deformations from the environment. On the other hand, muscles in musculoskeletal robots so far have faced challenges in generating force in such shapes and environments. To address this issue, we propose Patterned Structure Muscle (PSM), artificial muscles for musculoskeletal robots. PSM utilizes patterned structures with anisotropic characteristics, wire-driven mechanisms, and is made of flexible material Thermoplastic Polyurethane (TPU) using FDM 3D printing. This method enables the creation of various shapes of muscles, such as simple 1 degree-of-freedom (DOF) muscles, Multi-DOF wide area muscles, joint-covering muscles, and branched muscles. We created an upper arm structure using these muscles to demonstrate wide range of motion, lifting heavy objects, and movements through environmental contact. These experiments show that the proposed PSM is capable of operating in various shapes and environments, and is suitable for the muscles of musculoskeletal robots.

Design Method of a Kangaroo Robot with High Power Legs and an Articulated Soft Tail

In this paper, we focus on the kangaroo, which has powerful legs capable of jumping and a soft and strong tail. To incorporate these unique structure into a robot for utilization, we propose a design method that takes into account both the feasibility as a robot and the kangaroo-mimetic structure. Based on the kangaroo's musculoskeletal structure, we determine the structure of the robot that enables it to jump by analyzing the muscle arrangement and prior verification in simulation. Also, to realize a tail capable of body support, we use an articulated, elastic structure as a tail. In order to achieve both softness and high power output, the robot is driven by a direct-drive, high-power wire-winding mechanism, and weight of legs and the tail is reduced by placing motors in the torso. The developed kangaroo robot can jump with its hind legs, moving its tail, and supporting its body using its hind legs and tail.