The solution of the inverse kinematics problem of soft manipulators is essential to generate paths in the task space. The inverse kinematics problem of constant curvature or piecewise constant curvature manipulators has already been solved by using different methods, which include closed-form analytical approaches and iterative methods based on the Jacobian method. On the other hand, the inverse kinematics problem of nonconstant curvature manipulators remains unsolved. This study represents one of the first attempts in this direction. It presents both a modelbased method and a supervised learning method to solve the inverse statics of nonconstant curvature soft manipulators. In particular, a Jacobian-based method and a feedforward neural network are chosen and tested experimentally. A comparative analysis has been conducted in terms of accuracy and computational time.
This paper describes and discusses the preliminary results of a behavioural study on robot social acceptability, which was carried out during a public demonstration in South Korea. Data was collected by means of direct observation of people behaviour during interaction with robots. The most interesting result to emerge is that of young people: they tended to react to the robots presence with extreme curiosity and, quite often, to treat them aggressively. In this paper, the word bullying is used to describe any kind of improper and violent behaviour, intended to cause damages or impede the robot operation. It is the authors' opinion that if not tackled appropriately, abuses towards robots may become a serious hindrance to their future deployment, and safety. Hence, the necessity to tackle this issue with dedicated solutions during the early phases of design
This work describes the design and experimental results of an algorithm, designed to localize a gas source in an indoor environment with no strong airflow by using an autonomous agent. This condition exacerbates the patchiness and intermittency of odor distribution, typical of turbulent flows in the presence of strong mean flows. Furthermore, no information about the wind can be used to detect the position of the source. In the approach proposed here, the robot moves along spirals. A spiral can be reset and a new one started, based on the information acquired about gas distribution. This enables the robot to get close to the ejecting source, without relying on airflow measurements. Results from experiments are also described and discussed, to assess the efficiency of the proposed method.
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