Simultaneous Localization and Mapping (SLAM) is a vital task for autonomous robots moving in unknown environments. It is a rigorous and complex problem where the signals of different modalities originating from sensors as diverse as laser range finders, IR sensors, ultrasonic transducers, odometers and inertial measurement units are used in its different variants. Expensive sensory arrangements and significant computational resources are desired in all the variants of SLAM and multi-processing hardware-software arrangements are essentially needed. Consequently, the overall system becomes quite elaborate and expensive. Another common issue is the odometry error; this error accumulates over time and the robot looses track completely or distorts the map. Generally, a notebook computer is used as the computational resource; as it is frequently placed and removed from the robot, the odometry information is significantly affected. Therefore, it is desired to do the sensor calibration with fixed and complete system hardware. In this work, a testbed development for SLAM is reported. In this design, a low-cost and light-weight FPGA SoC development board is used as the main platform along with a low-cost LIDAR sensor; both fixed on the robot and controlled wirelessly. This fixes the whole hardware configuration and hence the weight of the robot, therefore the calibration results do not alter over time. Moreover, a HW-SW co-design approach is adopted to achieve a highly capable but very compact computational resource. Post-processing of the sensory data with rigorous calibration models has resulted in reasonably precise robot's odometry and environmental perception. The complete system is tested in indoor environment and satisfactory localization and mapping results are achieved.

The ECG (Electrocardiogram) signal reflects the electrical activity of the heart. Since amplitude of ECG signal is of order of few mV, it is susceptible to many types of noises and amongst which the most disturbing is power line interference (PLI). Variations in frequency of PLI further complicate the problem which can be taken care by implementation of adaptive notch filter (ANF). ANF normally requires a reference input which is not possible in all cases. In this paper, we have proposed an intelligent adaptive filter which does not require a reference input. Proposed method first detects the frequency of PLI noise then adaptively tracks and eliminates PLI from ECG signal.

Unlike wheeled robots, humanoid robots are able to overcome obstacles in the environment by stepping over or upon them. Conventional 2D methods for robot navigation fail to exploit this unique ability of humanoids and thus design trajectories only by circumventing obstacles. Recently, globalized algorithms have been presented that take into account this feature of humanoids. However, due to high computational complexity, most of them are very time consuming. In this paper we present a new approach to footstep planning in obstacle cluttered environments that employs a human-like strategy to terrain traversal. Simulation results of its implementation on a model of Saika-3 humanoid robot are also presented. The algorithm, being one of reactive nature, refutes previous claims that reactive algorithms fail to find successful paths in complex obstacle cluttered environments

Most of the control schemes developed for cooperation of multiple robots use centralized approach, hence the complexity of a system increases with an increase in the number of robots or complexity of an individual robot. Distributed control and event-based control approaches have been applied to a non-mobile multiple manipulator system with robots having only two degrees of freedom, while one of them is passive. Computer simulations show the applicability of these schemes for such a simple and under-actuated system. This paper extends the same discussion to a real-life experimental implementation. The results have proved the applicability of these control schemes for the proposed systems, and hence have opened new doors towards further research.

Many different control procedures and task execution strategies have been developed for multiple robots cooperation. Most of them are centralized and hence become very complex with increase in number of robots or their complexity. For this reason, the distributed control approach is found very attractive and the event-based control has enhanced its effectiveness. However, they demand the robots to be autonomous in all respects, and hence have found their applications for autonomous mobile robots or manipulator arms with abundant sensors and actuators. This paper, in contrast, has used these control approaches for a immobile multiple manipulator system with robots having only two degrees of freedom, while one of them is passive and with minimal sensory informations. Computer simulations show that it is also practicable to execute these schemes for an under-actuated system.