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The ‘boundary of space’ model representing all possible positions which may be occupied by a mechanism during its normal range of motion (for all positions and orientations) is called the work envelope. In the robotic domain, it is also known as the robot operating envelope or workspace. Several researchers have investigated workspace boundaries for different degrees of freedom (DOF), joint types and kinematic structures utilizing many approaches. The work envelope provides essential boundary information, which is critical for safety and layout concerns, but the work envelope information does not by itself determine the reach feasibility of a desired configuration. The effect of orientation is not captured as well as the coupling related to operational parameters. Included in this are spatial occupancy concerns due to linking multiple kinematic chains, which is an issue with multi-tasking machine tools, and manufacturing cells.

When performing trajectory planning for robotic applications, there are many aspects to consider, such as the reach conditions, joint and end-effector velocities, accelerations and jerk conditions, etc. The reach conditions are dependent on the end-effector orientations and the robot kinematic structure. The reach condition feasibility is the first consideration to be addressed prior to optimizing a solution. The ‘functional’ work space or work window represents a region of feasible reach conditions, and is a sub-set of the work envelope. It is not intuitive to define. Consequently, 2D solution approaches are proposed. The 3D travel paths are decomposed to a 2D representation via radial projections. Forward kinematic representations are employed to define a 2D boundary curve for each desired end effector orientation.

The purpose of this study is to provide an understanding of driver kinematics, injury mechanisms and spinal loads causing thoracolumbar spinal fractures in Indianapolis-type racing car drivers. Crash reports from 1996 to 2006, showed a total of forty spine fracture incidents with the thoracolumbar region being the most frequently injured (n=15). Seven of the thoracolumbar fracture cases occurred in the frontal direction and were a higher injury severity as compared to rear impact cases. The present study focuses on thoracolumbar spine fractures in Indianapolis-type racing car drivers during frontal impacts and was performed using driver medical records, crash reports, video, still photographic images, chassis accelerations from on-board data recorders and the analysis tool MADYMO to simulate crashes. A 50th percentile, male, Hybrid III dummy model was used to represent the driver.

A review of the existing mathematical models of a car occupant in a rear-end crash reveals that existing models inadequately describe the kinematics of the occupant and cannot demonstrate the injury mechanisms involved. Most models concentrate on head and neck motion and have neglected to study the interaction of the occupant with the seat back, seat cushion, and restraint systems. Major deficiencies are the inability to simulate the torso sliding up the seat back and the absence of the thoracic and lumbar spine as deformable, load transmitting members. The paper shows the results of a 78 degree-of-freedom model of the spine, head, and pelvis which has already been validated in +Gz and -Gx acceleration directions. It considers automotive-type restraint systems, seat back, and seat cushions, and the torso is free to slide up the seat back.

Spinal kinematics and kinetics of human cadaveric specimens subjected to -Gx acceleration are reported along with an attempt to design a surrogate spine for use in an anthropomorphic test device (ATD). There were a total of 30 runs on 9 embalmed and 2 unembalmed cadavers which were heavily instrumented. External photographic targets were attached to T1, T12, and the pelvis to record spinal kinematics. The subjects were restrained by upper and lower leg clamps attached to an impact seat equipped with a six-axis load cell. A rigid link 486 mm long and pinned at both ends was proposed for use in an ATD as a surrogate spine. An optimization method was used to obtain the location and length of a linkage which followed the least squares path of Tl relative to the pelvis.

The head acceleration pulses obtained from monkey concussion, cadaver skull fracture (t = 0.002 sec), and football helmet experiments (0.006< t< 0.011 sec) have been subjected to injury hazard assessment by the Severity Index method. Although not directly applicable, the method correlates well with degree of monkey concussion. The range of Severity Indices for acceleration pulses obtained during impact to nine cadavers, all of which produced a linear fracture, was 540-1760 (1000 is danger to life) with a median value of 910. The helmet experiments showed good correlation between the Severity Index and the Wayne State University tolerance curve. These helmet tests also showed that a kinematics chart with curves of velocity change, stopping distance, average head acceleration, and time, with a superimposed Wayne State tolerance curve, can be useful in injury assessment.

Normal motion of the lower limbs is discussed in this paper. The biomechanics of human gait has been studied experimentally using an instrumented walkway and analytically by means of mathematical models. Experimental methods for measuring ground reaction forces and limb kinematics are discussed. If limb kinematics are known, they can be used to compute the resultant joint forces and moments, using equations of motion which are algebraic in form. To obtain limb kinematics from the differential equations of motion, the problem is generally redundant, the degree of redundancy being equal to the number of unknown joint moments. The computation of muscle, ligament and bone contact forces from known resultant loads is also a redundant problem because there are more unknowns than there are available equations. For these there is no general consensus regarding the best objective function to be minimized.

Computational human body models, especially detailed finite element models are suitable for investigation of human body kinematic responses and injury mechanism. A real-world lateral vehicle-tree impact accident was reconstructed by using finite element method according to the accident description in the CIREN database. At first, a baseline vehicle FE model was modified and validated according to the NCAP lateral impact test. The interaction between the car and the tree in the accident was simulated using LS-Dyna software. Parameters that affect the simulation results, such as the initial pre-crash speed, impact direction, and the initial impact location on the vehicle, were analyzed. The parameters were determined by matching the simulated vehicle body deformations and kinematics to the accident reports.

A collaborative robot or cobot is a robot that can safely and effectively interact with human workers while performing industrial tasks. The ability to work alongside humans has increased the importance of collaborative robots in the automation industry, as this unique feature is a much needed property among robots nowadays. Rethink Robotics has pioneered this unique discipline by building many robots including the Baxter Robot which is exclusive not only because it has collaborative properties, but because it has two arms working together, each with 7 Degrees Of Freedom. The main goal of this research is to validate the kinematic equations for the Baxter collaborative robot and develop a unified reconfigurable kinematic model for the Left and Right arms so that the calculations can be simplified.

Inverse kinematic solutions of six degree of freedom (DOF) robot manipulation is a challenging task due to complex kinematic structure and application conditions which affects and depend on the robot’s tool frame position, orientation and different possible configurations. The robot trajectory represents a series of connected points in three dimensional space. Each point is defined with its position and orientation related to the robot’s base frames or users teach pendant. The robot will move from point to point using the desired motion type (linear, arc, or joint). This motion requires inverse kinematic solution. This paper presents a detailed inverse kinematic solution for Fanuc 6R (Rotational) robot family using a geometrical method. Each joint angular position will be geometrically analyzed and all possible solutions will be included in the decision equations. The solution will be developed in a parametric manner to cover the complete Fanuc six DOF family.

Animal-vehicle collision (AVC) is a significant safety issue on American roads. Each year approximately 1.5 million AVCs occur in the U.S., the majority of them involving deer. The increasing use of cameras and radar on vehicles provides opportunities for prevention or mitigation of AVCs, particularly those involving deer or other large animals. Developers of such AVC avoidance/mitigation systems require information on the behavior of encountered animals, setting characteristics, and driver response in order to design effective countermeasures. As part of a larger study, naturalistic driving data were collected in high AVC incidence areas using 48 participant-owned vehicles equipped with data acquisition systems (DAS). Continuous driving data including forward video, location information, and vehicle kinematics were recorded. The respective 11TB dataset contains 35k trips covering 360K driving miles.

The objective of this study was to investigate potential for traumatic brain injuries (TBI) using a newly developed, geometrically detailed, finite element head model (FEHM) within the concept of a simulated injury monitor (SIMon). The new FEHM is comprised of several parts: cerebrum, cerebellum, falx, tentorium, combined pia-arachnoid complex (PAC) with cerebro-spinal fluid (CSF), ventricles, brainstem, and parasagittal blood vessels. The model's topology was derived from human computer tomography (CT) scans and then uniformly scaled such that the mass of the brain represents the mass of a 50th percentile male's brain (1.5 kg) with the total head mass of 4.5 kg. The topology of the model was then compared to the preliminary data on the average topology derived from Procrustes shape analysis of 59 individuals. Material properties of the various parts were assigned based on the latest experimental data.

The kinematics of rear-end collisions based on published acceleration pulses of actual car-to-car collisions (10 and 23 mph) were reproduced on a crash simulator using anthropomorphic dummies, human cadavers, and a volunteer. Comparison of the responses of subjects without head support were based on the reactions developed at the base of the skull (occipital condyles). The cadavers gave responses which were representative of persons unaware of an impending collision. The responses of both dummies used were not comparable with those of the cadavers or volunteer, or to each other. An index based on voluntary human tolerance limits to statically applied head loads was developed and used to determine the severity of the simulations for the unsupported head cases. Results indicated that head torque rather than neck shear or axial forces is the major factor in producing neck injury.

A comparison is presented of the forces, accelerations, and kinematics of an anthropomorphic dummy for identical sled impacts for unrestrained, lap belted, and lap and diagonal chest restrained conditions. Biaxial accelerometers were mounted in the head, chest, and on the proximal end of the femur to obtain the accelerations during the impacts. Seat belt load cells were put in series with the belts at each anchor point. Biaxial load cells were positioned to be impacted by the head, chest, and each knee for the unrestrained condition and by the head and chest for the lap belted configuration. For the lap and diagonal chest restrained condition these load cells were not used. Impacts of 10 and 20 miles per hour were made with sled stopping distance of 4 and 9 inches, respectively. At 20 miles per hour the head struck with a force of 1580 pounds in the unrestrained mode, 600 pounds with the lap belt, and did not hit with the lap and shoulder harness.

Driver Assistance and Autonomous Driving features are becoming nearly ubiquitous in new vehicles. The intent of the Driver Assistant features is to assist the driver in making safer decisions. The intent of Autonomous Driving features is to execute vehicle maneuvers, without human intervention, in a safe manner. The overall goal of Driver Assistance and Autonomous Driving features is to reduce accidents, injuries, and deaths with a comforting driving experience. However, different drivers can react differently to advanced automated driving technology. It is therefore important to consider and improve the adaptability of these advances based on driver behavior. In this paper, a human-centric approach is adopted to provide an enriching driving experience. We perform data analysis of the naturalistic behavior of drivers when performing lane change maneuvers by extracting features from extensive Second Strategic Highway Research Program (SHRP2) data of over 5,400,000 data files.