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In archaeological use-wear analysis, the comparative study of stone tool artefacts and replicas from experiments provides evidence for their function. Thereby it helps to discover the behaviour and evolution of our prehistoric ancestors. However, major advancements in the methodology have been missing since decades. For example, identification of basic kinetic and dynamic parameters of the task motion such as force applied or duration of use is poorly reproducible; a satisfying characterization of the material treated by the tool is not yet possible. We propose a couple of methodological improvements with quantitative evaluation of the variables in use-wear analysis to overcome these limitations. At the centre of our revised methodology stands a robot arm serving as platform for innovative micro-wear experiments. The studies performed with our set-up provide advantages over those involving human subjects, as precise control of the task motion, reproducibility of the experimental conditions and ease of use appear superior. We combine our platform with focus-variation microscopy for topographic surface analysis of experimental replicas. Results with this approach demonstrate the advantage of highly controlled data for micro-wear analysis. We present the influence of force and duration on surface roughness, identifying duration as the dominant factor. To complement the characterization of experimental replicas, we developed a high resolution force sensor array to estimate the load distribution on the replica. The proposed sensor consists of a micro structured silicone membrane, which alters its optical properties when deforming under load. Presuming proper calibration, the force distribution can be inferred from optical photographs of the deformed membrane. We manufactured a sensor prototype for prove of concept studies. Next, we performed quantitative analysis of the human task motion by means of a motion capture system. The recorded trajectories serve as reference for the motion in our robot set-up. In addition, we show that the collected data can be used to deduce biomechanical implications for the user of the tool. In a first study, we compared the different motions between an expert and a non-expert during hide scraping. The results of a second study allowed the reconstruction of Neanderthals hunting behaviour. Wound marks of a cervid bone, dating to 120000 years before present, were analysed and compared with fracture patterns on reference bone targets after impacts with a thrusting spear. We correlated the observed features with the spear kinematics. Finally, we present a framework to generate complex motions for our robot set-up. Tasks relevant for use-wear analysis are characterized by contact switches and frictional contacts. Our approach aims for trajectory optimization with a soft contact model and regularized Coulomb friction to mimic contact interactions of the robot arm with the ground.

Reconstructing ancient technical gestures associated with simple tool actions is crucial for understanding the co-evolution of the human forelimb and its associated control-related cognitive functions on the one hand, and of the human technological arsenal on the other hand. Although the topic of gesture is an old one in Paleolithic archaeology and in anthropology in general, very few studies have taken advantage of the new technologies from the science of kinematics in order to improve replicative experimental protocols. Recent work in paleoanthropology has shown the potential of monitored replicative experiments to reconstruct tool-use-related motions through the study of fossil bones, but so far comparatively little has been done to examine the dynamics of the tool itself. In this paper, we demonstrate that we can statistically differentiate gestures used in a simple scraping task through dynamic monitoring. Dynamics combines kinematics (position, orientation, and speed) with contact mechanical parameters (force and torque). Taken together, these parameters are important because they play a role in the formation of a visible archaeological signature, use-wear. We present our new affordable, yet precise methodology for measuring the dynamics of a simple hide-scraping task, carried out using a pull-to (PT) and a push-away (PA) gesture. A strain gage force sensor combined with a visual tag tracking system records force, torque, as well as position and orientation of hafted flint stone tools. The set-up allows switching between two tool configurations, one with distal and the other one with perpendicular hafting of the scrapers, to allow for ethnographically plausible reconstructions. The data show statistically significant differences between the two gestures: scraping away from the body (PA) generates higher shearing forces, but requires greater hand torque. Moreover, most benchmarks associated with the PA gesture are more highly variable than in the PT gesture. These results demonstrate that different gestures used in ‘common’ prehistoric tasks can be distinguished quantitatively based on their dynamic parameters. Future research needs to assess our ability to reconstruct these parameters from observed use-wear patterns., PLoS ONE, 10 (8), ISSN:1932-6203