Approaches to human arm movement control—A review

Campos, Francisco M.; Calado, João Manuel Ferreira

doi:10.1016/j.arcontrol.2009.03.001

Cited by 47 publications

(24 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In such a simple task, there are infinite solutions for both the path of index finger and the trajectory of joints. However, many experimental evidences have shown that human has certain regularities [2]. Different models have been constructed in biophysics and psychology to find a principle that underlines the consistent human behavior.…”

Section: Related Workmentioning

confidence: 99%

“…They can be divided into two categories. The first is called descriptive models [2]. These laws and models, like the constrained minimum-jerk model [4], Fits Laws [5] and minimum jerk model [6], concern the kinematic properties of the finger movements.…”

Section: Related Workmentioning

confidence: 99%

“…Bernstein first stated this problem in 1967 and labeled it as the DOF problem in biophysics [3]. Since then, different computational models have been proposed to explain the intrinsic quality of human motion [2,[4][5][6][7]. In the field of conventional robotics, especially redundant manipulators, Bernstein problem is stated as inverse kinematics (IK) of robots.…”

Section: Introductionmentioning

confidence: 99%

“…In the field of biophysics and psychology, researches have been focused on finding the regularity of human movements. Human arm has a redundant structure, which enable it to have the freedom to choose kinematic and dynamic profile of the arm movement [2]. Bernstein first stated this problem in 1967 and labeled it as the DOF problem in biophysics [3].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Human-like motion planning for robotic arm system

Xie

Zhao

Liu

2011

2011 15th International Conference on Advanced Robotics (ICAR)

View full text Add to dashboard Cite

We explore the problem of human-like motion planning for robotic arms based on researches in biophysics, robotics and motion planning. Two common manipulation tasks, reaching point movement in obstacle free environment and reaching point movement through a narrow passage, are separately studied. First, we proposed a hypothesis named "Target Arm Pose" (TAP) to interpret the natural motion of human arm. Second, based on TAPs and the minimum jerk model, we develop a new robotic inverse kinematic algorithm in joint jerk level to conduct the reaching point movement in obstacle free environment. Furthermore, based on the new algorithm we utilize the redundancy of the robot to avoid joint velocity limits. Next, we use existing Bi-RRT algorithm combined with TAPs to implement the reaching point movement through a narrow passage. Finally, comparison between these two tasks and two algorithms is made to give a systematic analysis on the human-like motion planning problem. ). J J X T T (6) By differentiating Eq.(6) once more with respect to time:Now suppose that the joint jerk T satisfying Eq. (7) exists, then Eq.(7) can be replaced by:where ( 2 ) J J J X

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Human-like motion planning for robotic arm system

Xie

Zhao

Liu

2011

2011 15th International Conference on Advanced Robotics (ICAR)

View full text Add to dashboard Cite

show abstract

“…Singh et al [5] modeled reaching movements in the presence of obstacles and solved a stochastic optimal control problem that consists of probabilistic collision avoidance constraints and a cost function that trades off between effort and end-state variance in the presence of a signal-dependent noise. For more details, we refer the reader to Campos and Calado [6], Berret et al [7], and Mainprice et al [8].…”

Section: Introductionmentioning

confidence: 99%

Optimal Stochastic Control Problem for General Linear Dynamical Systems in Neuroscience

Chen

Deng

Yue

et al. 2017

Advances in Mathematical Physics

View full text Add to dashboard Cite

This paper considers a -dimensional stochastic optimization problem in neuroscience. Suppose the arm's movement trajectory is modeled by high-order linear stochastic differential dynamic system in -dimensional space, the optimal trajectory, velocity, and variance are explicitly obtained by using stochastic control method, which allows us to analytically establish exact relationships between various quantities. Moreover, the optimal trajectory is almost a straight line for a reaching movement; the optimal velocity bell-shaped and the optimal variance are consistent with the experimental Fitts law; that is, the longer the time of a reaching movement, the higher the accuracy of arriving at the target position, and the results can be directly applied to designing a reaching movement performed by a robotic arm in a more general environment.

show abstract