The gripping function in mechatronics and biomechanics.

Dolga, Valer ; Dolga, Lia

1. INTRODUCTION

The grip function is of main interest both for engineering- and for medical field, envisaging manipulation and manufacturing of various tools, or health care, injury prevention and physical rehabilitation. Improvement of the gripping skill, using an appropriate prosthesis recovers significantly the affected person's dexterity. As a result, both medical field and robotics require advanced physical gripping systems.

Mechatronics brought new openings for robotics. "New Robotics" employs ideas and principles from biology (Pfeifer et al., 2005). The synergy between fundamental science, engineering and medicine is constantly evolving while providing better tools and techniques. One can outline a parallelism biomechanics- biomechatronics- biorobotics.

The paper highlights the role of the mechatronic philosophy during the analysis, the design and the optimization stages of a biomedical- or robotic gripping system. A unique algorithm for creating and analysing gripping systems, based on the mechatronic approach, leads to a concurrent synergistic design.

2. THE GRIPPING ORGAN--THE HUMAN HAND --WITHIN BIOMECHANICS

Within biomechanics, the human hand is both a strong organ--as it executes the real prehension--and a delicate part because it might perform thin micro- motions. The human hand is also an essential sensorial organ that perceives, receives and transmits information (Fig. 1).

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The grip type varies with the shape, the size, the volume and the weight of the grasped objects, but it is also contingent with the force and the precision required by the motion. The relative weight coefficient for a reliable gripping condition is:

[delta] = load force/load hand (1)

A good quality gripping operation requires four properties: dexterity (configuration of grasping fingers), equilibrium (how hard to squeeze with the grasping fingers), stability and dynamic behaviour (Dario, 2000), (Barkat, 2009). The gripping force [F.sub.N] between the finger and the grasped object produces the friction force [F.sub.f] = [mu][F.sub.N], which acts in the same area and opposes to the motion (Fig. 2a). The friction coefficient u. corresponds to the finger- object contact. The dynamic behaviour of the gripped entity depends upon the kinematic parameters of the motion (speed, acceleration), the trajectory, and the massic parameters of the object, (Fig. 2b, c).

An optimal study of the human hand behaviour during the gripping process requires investigating the gripping force control (Fig. 3a). The central nervous system (CNS) receives, by the sensing organs, data about the size, shape, and material of the targeted object and estimates a force that might guarantee a secure gripping. The gripping force increases linearly toward the estimated value (Fig. 3b). The exteroceptive sensory system (the tactile sensors) detects incidental slides of the object inside the human hand; CNS collects the information very fast and orders the amplification of the gripping force to a new value. If no slide of the gripped object occurred, then the gripping force diminishes to a minimal required value. Next, the gripping force keeps a constant value and the control process contains thin micro-motions of the fingers over the contact area, not to break out the tactile information. The proprioceptive sensory system detects the internal status regarding the loading of the human hand "motor system".

Unavailability of a normal vision in reach-to-grasp motion alters the size of the grip aperture and the temporal features of the transport component (Connolly, 2008), (Rand, 2007).

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A complex configuration, with special parameters, typifies the biomechanical "actuator" of the human hand, since the mechanism that transmits the force encloses efficient joints, with an uninterrupted friction, and friction forces of low value. The parts inertia is low. Dead stroke and lost motion are absent.

The biomechanical analysis of the muscles studies the forces, the elasticity and the hysteresis and is essential for creating artificial systems very similar to the human hand.

In addition to the muscles, tendons, bones, joints and nerves, the human hand includes skin, one of the man's main innate sensors. Sensorially, the skin plays like a multiple convertor. The mecano--electrical convertor behaviour helps the CNS to detect whether the gripped object slides within the hand and to discover shapes and sizes of the gripped things. The piro--electrical convertor behaviour allows the sensing of the approximate temperature of the grasped object.

The human hand behaviour served as basis to define a mechatronic design procedure for artificial or hybrid (artificial- biological) systems, similar to the human hand.

3. THE MECHATRONIC DESIGN APPROACH OF A GRIPPER

Two features define the nature of the mechatronic systems:

* A functional level, broad, with 6 specific functions: the main function (with a transformation of an input into an output), the communication function, the protection function, the control function, the power function, the structural function;

* An organ level, with the organs that perform the functions of the system: sensor, computer system, actuator, power supply source, mechanism.

The decision about the structure of a mechatronic system complies with two principles from within the machine theory: the vertical causality principle (principle of cause and effect) and the principle of secondary functions (a set of secondary functions is always around the main function).

The innovative "mechatronic design philosophy" synergistically approaches the system design and maximizes the benefits reachable by an a priori integration of functionality with embedded microprocessor control (Amerongen 2007). Fig. 4 shows a fragment of how the developing principle was applied for the prosthesis / end effector system, where the energetic flow and the information flow were considered.

The structure of the mechatronic system (Fig. 5) aims at a superior systemic development. A partition based on the support function of each subsystem helps to target the aspect. Subsystems design solutions get more flexibility by shifting the implementation of functionality from mechanical hardware to computer software, while keeping the mechanical end-effectors.

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4. CONCLUSION

The paper outlines new opportunities for robotics & and biomechanics, focused on the gripping organ. The authors propose a structuring of the design process, starting from a parallelism biomechanics--mechatronics applied on the human hand. The configuration and the systemic development comply with the mechatronic design philosophy. The system optimization is still an open question for the authors.

Improving the mechatronic design procedure for robot- and for prosthesis grippers, involves better models and tools that facilitate simulation and virtual prototyping of multitechnological systems to which mechatronic systems belong.

5. REFERENCES

Amerongen, J. (2007). Mechatronic design--a port-based approach, Proceeding of the 4th International Symposium on Mechatronics and its Applications (ISMA07), pp ISMA7-1-8, ISSN 20080526144835, Sharjah, U.A.E. March 26-29, 2007

Barkat, B. et al. (2009). Optimization of grasping forces in handling of brittle objects Robotics and Autonomous Systems, Vol.54, Iss. 54, pp 460-468, ISSN 0921-8890

Connolly, J.& Goodale, M. (2008). The role of visual feedback of hand position in the control of manual prehension. Exp Brain Res. Revised 2008, pp 281-286, ISSN 10229019

Dario, F. (2000). Evolutionary Robotics--The Biology, Intelligence And Technology Of Self-organizing Machines, MIT Press, ISBN: 0262140705

Pfeifer, R.; Iida, F.& Bongard, J. (2005). New robotics: design principles for intelligent systems. Artificial life. 11(1-2): pp 99-120. ISSN: 1064-5462

Rand, M.; Lemay, M.; Squire, L.; Shimansky, Y.& Stelmach, G. (2007). Role of vision in aperture closure control during reach-to-grasp movements, Exp Brain Res., 2007,181 (3), pp 447-460, ISSN 0014-4819