Paulo José Costa

Abstract

Abstract

Abstract
Robots are increasingly present in our lives, sharing the workspace and tasks with human co-workers. However, existing interfaces for human-robot interaction / cooperation (HRI/C) have limited levels of intuitiveness to use and safety is a major concern when humans and robots share the same workspace. Many times, this is due to the lack of a reliable estimation of the human pose in space which is the primary input to calculate the human-robot minimum distance (required for safety and collision avoidance) and HRI/C featuring machine learning algorithms classifying human behaviours / gestures. Each sensor type has its own characteristics resulting in problems such as occlusions (vision) and drift (inertial) when used in an isolated fashion. In this paper, it is proposed a combined system that merges the human tracking provided by a 3D vision sensor with the pose estimation provided by a set of inertial measurement units (IMUs) placed in human body limbs. The IMUs compensate the gaps in occluded areas to have tracking continuity. To mitigate the lingering effects of the IMU offset we propose a continuous online calculation of the offset value. Experimental tests were designed to simulate human motion in a human-robot collaborative environment where the robot moves away to avoid unexpected collisions with de human. Results indicate that our approach is able to capture the human's position, for example the forearm, with a precision in the millimetre range and robustness to occlusions.

Abstract

Abstract
This article presents an innovative legged-wheeled system, designed to be applied in a hybrid robotic vehicle’s locomotion system, as its driving member. The proposed system will be capable to combine the advantages of legged and wheeled locomotion systems, having 3DOF connected through a combination of both rigid and non-rigid joints. This configuration provides the vehicle the ability to absorb impacts and selected external disturbances. A state space approach was adopted to control the joints, increasing the system’s stability and adaptability. Throughout this article, the entire design process of this robotic system will be presented, as well as its modeling and control. The proposed system’s design is biologically inspired, having as reference the human leg, resulting in the development of a prototype. The results of the testing process with the proposed prototype are also presented. This system was designed to be modular, low-cost, and to increase the autonomy of typical autonomous legged-wheeled locomotion systems.