Conference Paper

On the trajectory formation of the human arm constrained by the external environment

Sensorimotor Coordination Group, Max Planck Inst. for Psychol. Res., Munich, Germany
DOI: 10.1109/ROBOT.2003.1242030 Conference: Proceedings of the 2003 IEEE International Conference on Robotics and Automation, ICRA 2003, September 14-19, 2003, Taipei, Taiwan
Source: DBLP

ABSTRACT Opening a door, turning a steering wheel, rotating a coffee mill are typical examples of human movements constrained by the external environment. The constraints decrease the mobility of the human arm and leads to the redundancy in the distribution of the interaction force between the arm joints. Due to the redundancy of the force actuation in the constrained motions, there is infinite number of ways to form the trajectory of the arm. However, human forms the hand trajectory in a unique way. How does human resolve the redundancy of the constrained motions and specify the hand trajectory? To investigate these problems, we examine the trajectory of human arm in a crank rotation task. To explain the trajectory formation in constrained point-to-point motions, we formulate an optimal control problem and propose a novel criterion minimizing the hand contact force change and muscle force change over the time of movement. The simulation results are compared with human motion and force profiles obtained experimentally. It is shown that the novel criterion captures the characteristics of the human constrained motion much more satisfactory than conventional criteria accepted in the research community.

  • [Show abstract] [Hide abstract]
    ABSTRACT: This paper presents studies of the coordination of human upper body voluntary movement. A minimum-jerk 3D model is used to obtain the desired path in Cartesian space, which is widely used in the prediction of human reach movement. Instead of inverse kinematics, a direct optimization approach is used to predict each joint's profile (a spline curve). This optimization problem has four cost function terms: (1) Joint displacement function that evaluates displacement of each joint away from its neutral position; (2) Inconsistency function, which is the joint rate change (first derivative) and predicted overall trend from the initial target point to the final target point; (3) The non-smoothness function of the trajectory, which is the second derivative of the joint trajectory; (4) The non-continuity function, which consists of the amplitudes of joint angle rates at the initial and final target points, in order to emphasize smooth starting and ending conditions. This direct optimization technique can be used for potentially any number of degrees of freedom (DOF) system and it reduces the cost associated with certain inverse kinematics approaches for resolving joint profiles. This paper presents a high redundant upper-body modeling with 15 DOFs. Illustrative examples are presented and an interface is set up to visualize the results.
    Robotica 10/2006; 24(06):683 - 696. DOI:10.1017/S0263574706002852 · 0.88 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: A first step towards truly versatile robot assistants consists of building up experience with simple tasks such as the cooperative manipulation of objects. This paper extends the state-of-the-art by developing an assistant which actively cooperates during the point-to-point transportation of an object. Besides using admittance control to react to interaction forces generated by its operator, the robot estimates the intended human motion and uses this identified motion to move along with the operator. The offered level of assistance can be scaled, which is vital to give the operator the opportunity to gradually learn how to interact with the system. Experiments revealed that, while the robot is programmed to adapt to the human motion, the operator also adapts to the offered assistance. When using the robot assistant the required forces to move the load are greatly reduced and the operators report that the assistance feels comfortable and natural.
    2007 IEEE International Conference on Robotics and Automation, ICRA 2007, 10-14 April 2007, Roma, Italy; 01/2007
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Opening a door, turning a steering wheel, rotating a coffee mill are typical examples of human movements that require physical interaction with external environment. In these tasks, the human arm is kinematically constrained by the external environment. Although there are infinite possibilities for human subject to select his/her arm trajectories as well as interacting forces, experimental data of human constrained motion show that there exists some regulation inherent in all the measurement data. It is suggested in this paper that in the constrained movements human optimizes the criterion that minimizes the change of the hand contact forces as well as the muscle forces. This criterion differs from the minimum torque change criterion, predicting unconstrained reaching movements. Our experiments show close matching between the prediction and the subjects' data. Therefore, human may use different optimization strategies when performing constrained movements.