This paper exemplifies the design process for legged machines capable of dynamic behaviors. In order to achieve high performance robots, it is crucial to guarantee harmonious integration between software and hardware. Hence, the development of such capable robotic platforms must address design requirements that meet the assumptions of typical model-based controllers but also respect the physical limitations of a real system. First, we show that proper hardware design choices can greatly aid the control algorithm by approximating the physical robot to the template assumptions. We include actuation and sensing design examples that allows a simple model to capture a major portion of the natural dynamic behavior of the physical machine. Results are applied to a real robot (Figure 1) and we show that the adopted methodology is able to address typical problems in legged robots such as high bandwidth force control and robustness to impact. Finally, a simple model-based balance controller that takes advantage of the fidelity of the template model to the real machine is implemented. These are examples of software-hardware codesign processes that vastly facilitate robotic control.

This paper presents a method to achieve human and legged robot dynamic synchronization through bilateral feedback teleoperation. Our study shows how we can explore the interplay between human Extrapolated Center of Mass and the contact forces with the environment in order to transmit to the robot the underlying balancing and stepping strategy. All the necessary key equations for the frontal plane coupled dynamics are presented along with the human feedback law derived from the proposed state normalization in length and time. Here, we pay special attention to how the natural frequency of each system influences the resulting motion and analyze how the coupled system responds to various robot sizes. Experiments in which a human operator controls a simulated bipedal robot show how the Balance Feedback Interface force varies according to different scales and responds to external disturbances. Finally, we show the method's robustness to uneven terrain and how we can allow the point feet robot to synchronously take steps with the operator. This is an introductory study that aims to grant legged robots motor capabilities for power manipulation comparable to humans.

This paper presents the ongoing work towards enabling robots to achieve highly dynamic behavior through full-body teleoperation. Human operator and robot slave have independent balance controllers that interact with each other during the experiments. First we present a compliant balancing controller that regulates the feet contact forces in order to mitigate external disturbances and maintain balance. Next, by estimating the forces that the operator exerts over its own Center of Mass to generate movement, the Dynamic Synchronization Force Scaling controller allows the robot to anticipate human motion during posture tracking. This strategy requires reduced control gains for state tracking when compared to purely reactive controllers, resulting in an inherently more stable system. Results show a considerable reduction of the position tracking overshoot along with substantial reduction of required error-based control forces.

This paper presents the ongoing work towards enabling humanoid robots to achieve dynamic behaviors comparable to humans. By using the concept of Divergent Component of Motion (DCM) first in introduced in [1], the present paper permits operator and robot balance synchronization using the mutual dynamics of the Center of Mass (CoM) and Center of Pressure (CoP). The Linear Inverted Pendulum Model (LIPM) with a reaction mass [2] is utilized to capture the humanoid behavior which interacts with the human operator under the Equilibrium Point (EP) [3] control assumption. Remarkable similarities between the physical system behavior and simulated results suggest the feasibility of the strategy. Experiments conducted with the MIT HERMES humanoid robot further show the performance of the proposed method.

This paper introduces a novel Balance Feedback Interface (BFI) that addresses the problem of bilateral feedback for teleoperation of humanoid robots. With this new device we expect to enhance robot's high force manipulation performance to a level comparable to humans by dynamically synchronizing master and slave. Through this Human-Machine Interface (HMI) we aim to achieve two goals: (i) have the human pilot learn from the robot's dynamic behavior; and (ii) have the humanoid robotic platform learn from human's motor skills. The eventual goal is to fuse the teleoperator's commands and an autonomous controller for optimal performance. Initial results evaluate the stability of the robot while being teleoperated by a human pilot for a simple upright balancing task. During the experiment the user has no visual information about the robot's state and is expected to compensate for unpredicted instabilities. The bilateral feedback system shows robustness to inertial variations and to external disturbances with the proposed human-in-the-loop control strategy offering valuable insight for future work.