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We discuss novel human-centered intelligent spaces, specifically robotic elements which form the core of an interactive room that physically reconfigures: a robot-room. The proposed robot-room represents an advance in human-centered computing whereby human interaction is within a machine that physically envelops us. We discuss the motivation for such robot-rooms, and present initial work aimed at their physical realization. 

While robots are traditionally envisioned as physical entities that move through, sense, and act upon the environment, a new category is emerging: the inhabitable robot, or “robot-room,” which redefines human-robot interaction by immersing us within the robot itself. As a first step in exploring this novel design space, we developed a full-scale, rapidprototyped robot-room—not a simulation or scale model—and conducted a co-design study with 30 participants. Inside this immersive space, participants explored new forms of humanrobot interaction, engaging their perceptual faculties for “knowing spaces.” Our findings inform our ongoing development of a fully operational robot-room and offer valuable insights into expanding the concept of human-robot interaction to one of human-robot cohabitation. 

Compliant grasping is crucial for secure handling objects not only vary in shapes but also in mechanical properties. We propose a novel soft robotic gripper with decoupled stiffness and shape control capability for performing adaptive grasping with minimum system complexity. The proposed soft fingers conform to object shapes facilitating the handling of objects of different types, shapes, and sizes. Each soft gripper finger has a length constraining mechanism (an articulable rigid backbone) and is powered by pneumatic muscle actuators. We derive the kinematic model of the gripper and use an empirical approach to simultaneously map input pressures to stiffness control and bending deformation of fingers. We use these mappings to demonstrate decoupled stiffness and shape (bending) control of various grasping configurations. We conduct tests to quantify the grip quality when holding objects as the gripper changes orientation, the ability to maintain the grip as the gripper is subjected to translational and rotational movements, and the external force perturbations required to release the object from the gripper under various stiffness and shape (bending) settings. The results validate the proposed gripper's performance and show how the decoupled stiffness and shape control can improve the grasping quality in soft robotic grippers. 

Tendon actuated multisection continuum arms have high potential for inspection applications in highly constrained spaces. They generate motion by axial and bending deformations. However, because of the high mechanical coupling between continuum sections, variable length-based kinematic models produce poor results. A new mechanics model for tendon actuated multisection continuum arms is proposed in this paper. The model combines the continuum arm curve parameter kinematics and concentric tube kinematics to correctly account for the large axial and bending deformations observed in the robot. Also, the model is computationally efficient and utilizes tendon tensions as the joint space variables thus eliminating the actuator length related problems such as slack and backlash. A recursive generalization of the model is also presented. Despite the high coupling between continuum sections, numerical results show that the model can be used for generating correct forward and inverse kinematic results. The model is then tested on a thin and long multisection continuum arm. The results show that the model can be used to successfully model the deformation. 

Multisection continuum arms offer complementary characteristics to those of traditional rigid-bodied robots. Inspired by biological appendages, such as elephant trunks and octopus arms, these robots trade rigidity for compliance and accuracy for safety and, therefore, exhibit strong potential for applications in human-occupied spaces. Prior work has demonstrated their superiority in operation in congested spaces and manipulation of irregularly shaped objects. However, they are yet to be widely applied outside laboratory spaces. One key reason is that, due to compliance, they are difficult to control. Sophisticated and numerically efficient dynamic models are a necessity to implement dynamic control. In this paper, we propose a novel numerically stable center-of-gravity-based dynamic model for variable-length multisection continuum arms. The model can accommodate continuum robots having any number of sections with varying physical dimensions. The dynamic algorithm is of O(n2) complexity, runs at 9.5 kHz, simulates six to eight times faster than real time for a three-section continuum robot, and, therefore, is ideally suited for real-time control implementations. The model accuracy is validated numerically against an integral-dynamic model proposed by the authors and experimentally for a three-section pneumatically actuated variable-length multisection continuum arm. This is the first sub-real-time dynamic model based on a smooth continuous deformation model for variable-length multisection continuum arms. 

In this paper, we propose and investigate a new approach to modeling variable curvature continuum robot sections, based on Euler spirals. Euler spirals, also termed Clothoids, or Cornu spirals, are those curves in which the curvature increases linearly with their arc length. In this work, Euler spirals are applied to the kinematic modeling of continuum robots for the first time. The approach was evaluated using the sections of numerous continuum robots, including two novel parallel continuum robots. Each robot consists of three parallel sections, each with three thin, long McKibben actuators. These sections are poorly modeled by the widely used constant curvature kinematic model. The constant curvature and Euler spiral models were compared and the Euler spiral method was seen to be a significantly better match for a wide range of configurations of the robot hardware.