Hongxing Wei

Sambot: A Self-Assembly Modular Robot System

The design and structure of a self-assembly modular robot (Sambot) are presented in this paper. Each module has its own autonomous mobility and can connect with other modules to form robotic structures with different manipulation abilities. Sambot has a versatile, robust, and flexible structure. The computing platform provided for each module is distributed and consists of a number of interlinked microcontrollers. The interaction and connectivity between different modules is achieved through infrared sensors and Zigbee wireless communication in discrete state and control area network bus communication in robotic configuration state. A new mechanical design is put forth to realize the autonomous motion and docking of Sambots. It is a challenge to integrate actuators, sensors, microprocessors, power units, and communication elements into a highly compact and flexible module with the overall size of 80 mm × 80 mm × 102 mm. The work describes represents a mature development in the area of self-assembly distributed robotics.

An Adaptive-Gain Complementary Filter for Real-Time Human Motion Tracking With MARG Sensors in Free-Living Environments

High-resolution, real-time data obtained by human motion tracking systems can be used for gait analysis, which helps better understanding the cause of many diseases for more effective treatments, such as rehabilitation for outpatients or recovery from lost motor functions after a stroke. In order to achieve real-time ambulatory human motion tracking with low-cost MARG (magnetic, angular rate, and gravity) sensors, a computationally efficient and robust algorithm for orientation estimation is critical. This paper presents an analytically derived method for an adaptive-gain complementary filter based on the convergence rate from the Gauss-Newton optimization algorithm (GNA) and the divergence rate from the gyroscope, which is referred as adaptive-gain orientation filter (AGOF) in this paper. The AGOF has the advantages of one iteration calculation to reduce the computing load and accurate estimation of gyroscope measurement error. Moreover, for handling magnetic distortions especially in indoor environments and movements with excessive acceleration, adaptive measurement vectors and a reference vector for earths magnetic field selection schemes are introduced to help the GNA find more accurate direction of gyroscope error. The features of this approach include the accurate estimation of the gyroscope bias to correct the instantaneous gyroscope measurements and robust estimation in conditions of fast motions and magnetic distortions. Experimental results are presented to verify the performance of the proposed method, which shows better accuracy of orientation estimation than several well-known methods.

Sambot: A self-assembly modular robot for swarm robot

This paper presents a novel self-assembly modular robot (Sambot) that also shares characteristics with self-reconfigurable and self-assembly and swarm robots. Each Sambot can move autonomously and connect with the others. Multiple Sambot can be self-assembled to form a robotic structure, which can be reconfigured into different configurable robots and can locomote. A novel mechanical design is described to realize function of autonomous motion and docking. Introducing embedded mechatronics integrated technology, whole actuators, sensors, microprocessors, power and communication unit are embedded in the module. The Sambot is compact and flexble, the overall size is 80×80×102mm. The preliminary self-assembly and self-reconfiguration of Sambot is discussed, and several possible configurations consisting of multiple Sambot are designed in simulation environment. At last, the experiment of self-assembly and self-reconfiguration and locomotion of multiple Sambot has been implemented.

A Real-Time Cardiac Arrhythmia Classification System with Wearable Sensor Networks

Long term continuous monitoring of electrocardiogram (ECG) in a free living environment provides valuable information for prevention on the heart attack and other high risk diseases. This paper presents the design of a real-time wearable ECG monitoring system with associated cardiac arrhythmia classification algorithms. One of the striking advantages is that ECG analog front-end and on-node digital processing are designed to remove most of the noise and bias. In addition, the wearable sensor node is able to monitor the patients ECG and motion signal in an unobstructive way. To realize the real-time medical analysis, the ECG is digitalized and transmitted to a smart phone via Bluetooth. On the smart phone, the ECG waveform is visualized and a novel layered hidden Markov model is seamlessly integrated to classify multiple cardiac arrhythmias in real time. Experimental results demonstrate that the clean and reliable ECG waveform can be captured in multiple stressed conditions and the real-time classification on cardiac arrhythmia is competent to other workbenches.

Staying-alive and energy-efficient path planning for mobile robots

As most mobile robots are powered by batteries, their energy and operation times are limited. Therefore, how to minimize energy consumption and keep mobile robots to stay alive becomes an important problem. In this paper, by applying a dynamic energy-evaluation scheme, in which we consider if a robot has enough energy to go to next location, finish the task and return to the docking station in the path planning, we propose two staying-alive and energy-efficient path planning approaches based on the greedy TSP and Tabu-search methods, respectively. The experimental results show that our Tabu-search-based approach is the best and can provide an effective path planning by which a robot can be guaranteed to stay alive and finish all tasks with the minimum energy.

Implementing Hybrid Operating Systems with Two-Level Hardware Interrupts

In this paper, we propose to implement hybrid operating systems based on two-level hardware interrupts. To separate real-time and non-real-time hardware interrupts by hardware, we show that it is easier to build up hybrid systems with better performance. We analyze and discuss the key issues for implementing a hybrid system based on this and implement a hybrid system called RTLinux-THIN (Real-Time LINUX with Two-level Hardware Interrupts) on the ARM architecture by combining ARM Linux kernel 2.6.9 and muC/OS-II. We conduct experiments on a set of real application programs including mplayer [20], Bonnie [4] and iperf [13] and compare the interrupt latency distributions for RTLinux-THIN (with and without cache locking), RTAI and Linux on a hardware platform based on Intel PXA270processor [12]. The experimental results show that RTLinux-THIN improves real-time interrupt latencies and provides better predictability.

Look-Ahead Algorithm with Whole S-Curve Acceleration and Deceleration

Tool paths of a complex contour machining generated by commercial CAD/CAM systems are mainly composed of many short linear/circular blocks. Though the look-ahead algorithms can improve speed and accuracy in the machining of short linear/circular segments, most of them just deal with linear segments with trapezoid acceleration and deceleration (acc/dec). In addition, the look-ahead algorithms with S-curve acc/dec are too complex to adopt the equivalent S-curve profile by approximation algorithm. To increase the smoothness of feedrate profile and machining efficiency of continuous short line and circle machining, this paper presents a feedrate profile generation approach and corresponding look-ahead algorithm with whole S-curve acc/dec. With the proposed look-ahead scheme, the feedrate profiles with S-curve acc/dec can work efficiently in a lot of short line and circle segments. Thus, the machining productivity can be increased and the feedrate profiles are smooth. The simulation and experiments verify the feasibility and validity of the proposed approach.

RT-ROS

ROS, an open-source robot operating system, is widely used and rapidly developed in the robotics community. However, running on Linux, ROS does not provide real-time guarantees, while real-time tasks are required in many robot applications such as robot motion control. This paper for the first time presents a real-time ROS architecture called RT-RTOS on multi-core processors. RT-ROS provides an integrated real-time/non-real-time task execution environment so real-time and non-real-time ROS nodes can be separately run on a real-time OS and Linux, respectively, with different processor cores. In such a way, real-time tasks can be supported by real-time ROS nodes on a real-time OS, while non-real-time ROS nodes on Linux can provide other functions of ROS. Furthermore, high performance is achieved by executing real-time ROS nodes and non-real-time ROS nodes on different processor cores. We have implemented RT-ROS on a dual-core processor and conducted various experiments with real robot applications. The experimental results show that RT-ROS can effectively provide real-time support for the ROS platform with high performance by exploring the multi-core architecture.

Swarm Robots

Inspired by the swarm behaviours of social insects, research into the self-assembly of swarm robots has become an attractive issue in the robotic community. Unfortunately, there are very few platforms for self-assembly and locomotion in the field of swarm robotics. The Sambot is a novel self-assembling modular robot that shares characteristics with swarm robots and self-reconfigurable robots. Each Sambot can move autonomously and connect with the other. This paper discusses the concept of combining self-assembly and locomotion for swarm robots. Distributed control algorithms for self-assembly and locomotion are proposed. Using five physical Sambots, experiments were carried out on autonomous docking, self-assembly and locomotion. Our control algorithm for self-assembly can also be used to realize the autonomous construction and self-repair of robotic structures consisting of a large number of Sambots.

The distributed control and experiments of directional self-assembly for modular swarm robots

Self-assembly is a process during which pre-existing components are autonomously organized into some special patterns or structures without human intervention. In this paper, we propose a new control algorithm on distributed self-assembly which is implemented on the Sambot robot platform. A directional self-assembly control model is proposed, in which a configuration connection state table is used to represent the configuration of the robotic structures composed of multiple Sambots. There are three types of Sambots, docking Sambots, SEED Sambot and Connected Sambots. All docking Sambots adopt behavior-based controller that is independent of target configuration. The SEED Sambot and Connected Sambots are used to implement configuration growth. Self-assembly experiments of snake-like and quadruped configurations are conducted on the Sambot platform with five Sambots. The experimental results show the effectiveness and scalability of the distributed self-assembly algorithm.