Robotic trajectory tracking for neurological rehabilitation

Model Free Adaptive Control for Robotic Manipulator Trajectory Tracking

This paper considers the problem of trajectory tracking of robotic manipulator system by using model free adaptive control (MFAC). The dynamic linearization technique is first introduced, and then the controller can be designed only by I/O data of the robotic manipulator system via MFAC approach, not includes any explicit model information. With some given conditions for controller parameters, ...

Trajectory Generation and Tracking of a 5-dof Robotic Arm

The main problem in trajectory generation and tracking of robotic manipulators is to plan the trajectory and compute the required joint angles. Inverse kinematics modelling is usually adopted, though sometimes other approaches are needed due to the lack of reliability and accuracy of analytical methods. This paper presents a comparison between an analytical inverse kinematics based hybrid appro...

Optimizing robotic actuator, trajectory tracking and fuzzy control PhD Thesis

Optimal Trajectory Generation for a Robotic Worm via Parameterization by B-Spline Curves

In this paper we intend to generate some set of optimal trajectories according to the number of control points has been applied for parameterizing those using B-spline curves. The trajectories are used to generate an optimal locomotion gait in a crawling worm-like robot. Due to gait design considerations it is desired to minimize the required torques in a cycle of gait. Similar to caterpillars,...

Neurological Rehabilitation

Thehumanmotor systemhas the capacity to learn through practice and experience. Motor learning is a loosely defined term that encompassesmotor adaptation, skill acquisition, anddecision-making (Shadmehr andWise, 2005; Krakauer, 2006; Krakauer and Mazzoni, 2011; Wolpert et al., 2011). This chapter will focus on what we, and others, consider to be twodistinct types ofmotor learning (Agostino et al...