Teleoperation—i.e., controlling a robot with human motion—proves promising in enabling a humanoid robot to move as dynamically as a human. But how to map human motion to a humanoid robot matters because a human and a humanoid robot rarely have identical topologies and dimensions. This work presents an experimental study that utilizes reaction tests to compare joint space and task space mappings for dynamic teleoperation of an anthropomorphic robotic arm that possesses human-level dynamic motion capabilities. The experimental results suggest that the robot achieved similar and, in some cases, human-level dynamic performances with both mappings for the six participating human subjects. All subjects became proficient at teleoperating the robot with both mappings after practice, despite that the subjects and the robot differed in size and link length ratio and that the teleoperation required the subjects to move unintuitively. Yet, most subjects developed their teleoperation proficiencies more quickly with task space mapping than with joint space mapping after similar amounts of practice. This study also indicates the potential values of three-dimensional task space mapping, a teleoperation training simulator, and force feedback to the human pilot for intuitive and dynamic teleoperation of a humanoid robot’s arms.
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Bipedal Robot Walking Control Using Human Whole-Body Dynamic Telelocomotion
For humanoids to be deployed in demanding situations, such as search and rescue, highly intelligent decision making and proficient sensorimotor skill is expected. A promising
solution is to leverage human prowess by interconnecting robot
and human via teleoperation. Towards creating seamless operation, this paper presents a dynamic telelocomotion framework
that synchronizes the gait of a human pilot with the walking
of a bipedal robot. First, we introduce a method to generate
a virtual human walking model from the stepping behavior of
a human pilot which serves as a reference for the robot to
walk. Second, the dynamics of the walking reference and robot
walking are synchronized by applying forces to the human pilot
and the robot to achieve dynamic similarity between the two
systems. This enables the human pilot to continuously perceive
and cancel any asynchrony between the walking reference and
robot. A consistent step placement strategy for the robot is
derived to maintain dynamic similarity through step transitions.
Using our human-machine-interface, we demonstrate that the
human pilot can achieve stable and synchronous teleoperation of a simulated robot through stepping-in-place, walking,
and disturbance rejection experiments. This work provides a
fundamental step towards transferring human intelligence and
reflexes to humanoid robots.
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- Award ID(s):
- 2043339
- NSF-PAR ID:
- 10397678
- Date Published:
- Journal Name:
- IEEE International Conference on Robotics and Automation
- ISSN:
- 1049-3492
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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null (Ed.)Teleoperation—i.e., controlling a robot with human motion—proves promising in enabling a humanoid robot to move as dynamically as a human. But how to map human motion to a humanoid robot matters because a human and a humanoid robot rarely have identical topologies and dimensions. This work presents an experimental study that utilizes reaction tests to compare joint space and task space mappings for dynamic teleoperation of an anthropomorphic robotic arm that possesses human-level dynamic motion capabilities. The experimental results suggest that the robot achieved similar and, in some cases, human-level dynamic performances with both mappings for the six participating human subjects. All subjects became proficient at teleoperating the robot with both mappings after practice, despite that the subjects and the robot differed in size and link length ratio and that the teleoperation required the subjects to move unintuitively. Yet, most subjects developed their teleoperation proficiencies more quickly with task space mapping than with joint space mapping after similar amounts of practice. This study also indicates the potential values of three-dimensional task space mapping, a teleoperation training simulator, and force feedback to the human pilot for intuitive and dynamic teleoperation of a humanoid robot’s arms.more » « less
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Abstract This paper explores the kinematic synthesis, design, and pilot experimental testing of a six-legged walking robotic platform able to traverse through different terrains. We aim to develop a structured approach to designing the limb morphology using a relaxed kinematic task with incorporated conditions on foot-environments interaction, specifically contact force direction and curvature constraints, related to maintaining contact. The design approach builds up incrementally starting with studying the basic human leg walking trajectory and then defining a “relaxed” kinematic task. The “relaxed” kinematic task consists only of two contact locations (toe-off and heel-strike) with higher-order motion task specifications compatible with foot-terrain(s) contact and curvature constraints in the vicinity of the two contacts. As the next step, an eight-bar leg image is created based on the “relaxed” kinematic task and incorporated within a six-legged walking robot. Pilot experimental tests explore if the proposed approach results in an adaptable behavior which allows the platform to incorporate different walking foot trajectories and gait styles coupled to each environment. The results suggest that the proposed “relaxed” higher-order motion task combined with the leg morphological properties and feet material allowed the platform to walk stably on the different terrains. Here we would like to note that one of the main advantages of the proposed method in comparison with other existing walking platforms is that the proposed robotic platform has carefully designed limb morphology with incorporated conditions on foot-environment interaction. Additionally, while most of the existing multilegged platforms incorporate one actuator per leg, or per joint, our goal is to explore the possibility of using a single actuator to drive all six legs of the platform. This is a critical step which opens the door for the development of future transformative technology that is largely independent of human control and able to learn about the environment through their own sensory systems.more » « less
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Whole-body control (WBC) is a generic task-oriented control method for feedback control of loco-manipulation behaviors in humanoid robots. The combination of WBC and model-based walking controllers has been widely utilized in various humanoid robots. However, to date, the WBC method has not been employed for unsupported passive-ankle dynamic locomotion. As such, in this article, we devise a new WBC, dubbed the whole-body locomotion controller (WBLC), that can achieve experimental dynamic walking on unsupported passive-ankle biped robots. A key aspect of WBLC is the relaxation of contact constraints such that the control commands produce reduced jerk when switching foot contacts. To achieve robust dynamic locomotion, we conduct an in-depth analysis of uncertainty for our dynamic walking algorithm called the time-to-velocity-reversal (TVR) planner. The uncertainty study is fundamental as it allows us to improve the control algorithms and mechanical structure of our robot to fulfill the tolerated uncertainty. In addition, we conduct extensive experimentation for: (1) unsupported dynamic balancing (i.e., in-place stepping) with a six-degree-of-freedom biped, Mercury; (2) unsupported directional walking with Mercury; (3) walking over an irregular and slippery terrain with Mercury; and 4) in-place walking with our newly designed ten-DoF viscoelastic liquid-cooled biped, DRACO. Overall, the main contributions of this work are on: (a) achieving various modalities of unsupported dynamic locomotion of passive-ankle bipeds using a WBLC controller and a TVR planner; (b) conducting an uncertainty analysis to improve the mechanical structure and the controllers of Mercury; and (c) devising a whole-body control strategy that reduces movement jerk during walking.more » « less
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