Hardware accelerated image processing on FPGA based PYNQ-Z2 board

In this paper we present the partial results of a research in progress made in order to develop a prototype of a self-driving car’s controller and processing unit. The framework that we used consisted of a camera for input of visual imagery information (Logitech 720p), a laser range finder for depth and object sensing (Parallax; PulsedLight LIDAR-Lite v2), and the main processing board, an FPGA based accelerator board PYNQ Z2.

Development of a Mobile Robot That Plays Tag with Touch-and-Away Behavior Using a Laser Range Finder

The development of robots that play with humans is a challenging topic for robotics. We are developing a robot that plays tag with human players. To realize such a robot, it needs to observe the players and obstacles around it, chase a target player, and touch the player without collision. To achieve this task, we propose two methods. The first one is the player tracking method, by which the robot moves towards a virtual circle surrounding the target player. We used a laser range finder (LRF) as a sensor for player tracking. The second one is a motion control method after approaching the player. Here, the robot moves away from the player by moving towards the opposite side to the player. We conducted a simulation experiment and an experiment using a real robot. Both experiments proved that with the proposed tracking method, the robot properly chased the player and moved away from the player without collision. The contribution of this paper is the development of a robot control method to approach a human and then move away safely.

Efficient Non-Odometry Method for Environment Mapping and Localisation of Mobile Robots

The paper presents the simple algorithm of simultaneous localisation and mapping (SLAM) without odometry information. The proposed algorithm is based only on scanning laser range finder. The theoretical foundations of the proposed method are presented. The most important element of the work is the experimental research. The research underlying the paper encompasses several tests, which were carried out to build the environment map to be navigated by the mobile robot in conjunction with the trajectory planning algorithm and obstacle avoidance.

Development and Experimental Verification of a Person Tracking System of Mobile Robots Using Sensor Fusion of Inertial Measurement Unit and Laser Range Finder for Occlusion Avoidance

The authors have been developing a mobile robot to assist doctors in hospitals in managing medical tools and patient electronic medical records. The robot tracks behind a mobile medical worker while maintaining a constant distance from the worker. However, it was difficult to detect objects in the sensor’s invisible region, called occlusion. In this study, we propose a sensor fusion method to estimate the position of a robot tracking target indirectly by an inertial measurement unit (IMU) in addition to the direct measurement by an laser range finder (LRF) and develop a human tracking system to avoid occlusion by a mobile robot. Based on this, we perform detailed experimental verification of tracking a specified person to verify the validity of the proposed method.