Abstract-The requirement to scope and analyze hidden parts of the human body and the limitations of current imaging technologies is motivating the development of novel approaches. In clinical PET/CT systems, the attenuation and activity maps of the studied body region are recovered from measurements. However, the modeling of Compton scattering enables to obtain the attenuation map through the electron density directly from transmission data, thus obviating the need of a CT scan. In this context, a bimodality imaging approach (gamma-ray transmission/emission imaging) using scattered radiation referred to as Compton scattering tomography (CST) is presented. This concept is modeled by two generalized Radon transforms and proposes to reconstruct the electron density, the attenuation map, and the activity concentration of the studied body region. Simulation results demonstrate the feasibility and viability of this novel imaging concept. The present approach could be an interesting alternative to current tomographic imaging techniques.

Motion planning is a major component of any automated driving system. The safety assessment of such components requires a formal characterization of the perception and control mechanisms. This requires dedicated tools and models for the environment, sensors and vehicles that are highly representative of the real world. Simulation is a method to virtually investigate the behavior of systems under study. It has a key role to play in demonstrating the safety of autonomous vehicles. In this context, we consider a control module as a black-box and try to determine a reference which represents the 'right decision', if it exists. An optimization-based reference model is created for the control function. This model allows each scene in the environment to be mapped to the desired decision regardless of the black-box. The black-box and the reference model are run on several critical scenarios. In output, an assessment of decision making is performed along with systematic criticality characterization of targeted scenarios.

In this paper we report results on benchmarking a HRP-2 humanoid robot. The humanoid robots of this serie are known to be very robust. They have been successfully used by several research groups for the design of new motion generation algorithms. As such it is a reference in the category of electrically driven humanoid robot. As new humanoid robots are continuously built it is interesting to compare the performances of these new prototypes to those of HRP-2. This benchmarking study was realized through a campaign of measurements in an advanced equipped testing laboratory that provides a well adapted controlled environment. We have investigated the effect of temperatures variation on the robot walking capabilities. In order to benchmark various environmental conditions and algorithms we computed a set of performance indicators for bipedal locomotion. The scope of the algorithms for motion generation evaluated here ranges from analytical solution to numerical optimization approach, enabling real-time walking or multi-contacts motions.