Comparison of Impulses Experienced on Human Joints Walking on the Ground to Those Experienced Walking on a Treadmill

It has been reported that long-term exercise on a treadmill (running machine) may cause injury to the joints in a human's lower extremities. Previous works related to analysis of human walking motion are, however, mostly based on clinical statistics and experimental methodology. This paper proposes an analytical methodology. Specifically, this work deals with a comparison of normal walking on the ground and walking on a treadmill in regard to the external and internal impulses exerted on the joints of a human's lower extremities. First, a modeling procedure of impulses, impulse geometry, and impulse measure for the human lower extremity model will be briefly introduced and a new impulse measure for analysis of internal impulse is developed. Based on these analytical tools, we analyze the external and internal impulses through a planar 7-linked human lower extremity model. It is shown through simulation that the human walking on a treadmill exhibits greater internal impulses on the knee and ankle joints of the supporting leg when compared to that on the ground. In order to corroborate the effectiveness of the proposed methodology, a force platform was developed to measure the external impulses exerted on the ground for the cases of the normal walking and walking on the treadmill. It is shown that the experimental results correspond well to the simulation results

Utilization of Inertial Effect in Damping-based Posture Control of Mobile Manipulator

This paper presents the utilization of inertial effect in damping-based posture control of a mobile manipulator. As a measure for redundancy resolution of a mobile manipulator, an effective inertia at the end effector in the operational space is proposed and investigated. By changing the effective inertia property via null-motion, we can get the reduced inertial property of the mobile manipulator. The reduced effective inertia has a significant effect on reducing the impulse force in collision with environment. To find a posture satisfying both the reduced inertia and joint limit constraints, we propose a combined potential function method which can deal with multiple constraints. The proposed reduced inertia property algorithm is integrated into a damping controller to reduce the impulse force at collision and to regulate the contact force in mobile manipulation. 1

Learning manipulative skills using an artificial intelligence approach.

The aim of this research was to design a non-linear controller based on an Artificial Neural Network and Reinforcement Learning algorithms implementation, which is able to perform an intelligent robotic assembly of mechanical components. Different information was applied and combined to develop a fully unsupervised, intelligent controller. In the author's design no class labelling or geometry feature pretraining takes place. Only force and torque signals together with the direction of insertion were supplied to the controller. A unique sandwich structure of the intelligent controller was proposed. It featured two major layers, a State Recognition module where the detection and localisation of the contact points were performed, and the Decision Making subsystem where the decision about the next action took place.All the algorithms were implemented and tested on simulated data before being applied to the real-life peg-in-hole insertion. The results are presented in the form of graphs and tables.Evaluation of the environmental uncertainty was accomplished. The signal from the force and torque sensor was acquired under controlled conditions. All the data was collected to establish the area and level of uncertainty (e.g. signal errors) the artificial controller would need to learn to cope with and compensate for.The empirical part of the thesis includes the investigation into the effects of different learning methods applied on the same geometry. The influence of action-selection methods on AI agent performance was analysed. The proposed controller was applied to a set of real life peg-and-hole experiments. Both circular and square peg geometries were used, and insertions into chamfered and non-chamfered holes were performed. Materials with different friction factors were used for mating parts.Fast and stable knowledge acquisition was clearly present in all the cases investigated. A significant reduction in contact force value during the initial stage of the learning process was recorded. The force was usually reduced to one tenth of the initial value. Some fluctuations were recorded but when the cylindrical peg was considered the value of contact forces never exceeded 0.5 N during the steady state