Mast Cell Tumors

Mast cell tumor is one of the major cutaneous tumors in dogs. Though the etiology of MCTs is not completely understood, it becomes clear that approximately 10–20% MCTs express mutant KIT receptors with ligand‐independent phosphorylation. Tyrosine kinase inhibitors targeting KIT exert antitumor effects on malignant proliferation of mast cells with or without gene mutations. However, the efficacy of KIT inhibitors on dogs with MCTs has been limited. In this chapter, we would like to outline the general understandings of mast cells such as the process of its differentiation and proliferation, and what has been revealed regarding the mechanism of tumorigenesis and therapeutic approaches. In particular, KIT mutation‐related evidences and therapeutic approaches in the future are discussed

Development and Control of Articulated Mobile Robot for Climbing Steep Stairs

In this paper, we develop an articulated mobile robot that can climb stairs, and also move in narrow spaces and on 3-D terrain. This paper presents two control methods for this robot. The first is a 3-D steering method that is used to adapt the robot to the surrounding terrain. In this method, the robot relaxes its joints, allowing it to adapt to the terrain using its own weight, and then, resumes its motion employing the follow-the-leader method. The second control method is the semi-autonomous stair climbing method. In this method, the robot connects with the treads of the stairs using a body called a connecting part, and then shifts the connecting part from its head to its tail. The robot then uses the sensor information to shift the connecting part with appropriate timing. The robot can climb stairs using this method even if the stairs are steep, and the sizes of the riser and the tread of the stairs are unknown. Experiments are performed to demonstrate the effectiveness of the proposed methods and the developed robot

Sensor based navigation for car-like mobile robots using generalized Voronoi graph

Our research objective is to realize sensor based navigation by car-like mobile robots. The generalized Voronoi graph (GVG) can describe a mobile robot's path for sensor based navigation from the point of view of completeness and safety. However, it is impossible to apply the path to a car-like mobile robot directly, because limitation of the minimum turning radius prevents following the non-smooth GVG. To solve the problem, we propose a local smooth path planning algorithm for car-like mobile robots. Basically, an initial path is generated by a conventional path planning algorithm using GVG theory, and it is deformed smoothly to enable car-like robots' following by maximizing an evaluation function proposed in the paper. The key topics are: definition of our evaluation function; and how to modify the GVG. We introduce a local smooth path planning algorithm based on the GVG, and explain a detail of the evaluation function. Simulation results support validity of the algorithm </p