Surya P. N. Singh

V-REP: A versatile and scalable robot simulation framework

From exploring planets to cleaning homes, the reach and versatility of robotics is vast. The integration of actuation, sensing and control makes robotics systems powerful, but complicates their simulation. This paper introduces a versatile, scalable, yet powerful general-purpose robot simulation framework called V-REP. The paper discusses the utility of a portable and flexible simulation framework that allows for direct incorporation of various control techniques. This renders simulations and simulation models more accessible to a general-public, by reducing the simulation model deployment complexity. It also increases productivity by offering built-in and ready-to-use functionalities, as well as a multitude of programming approaches. This allows for a multitude of applications including rapid algorithm development, system verification, rapid prototyping, and deployment for cases such as safety/remote monitoring, training and education, hardware control, and factory automation simulation.

System Design of a Quadrupedal Galloping Machine

In this paper we present the system design of a machine that we have constructed to study a quadrupedal gallop gait. The gallop gait is the preferred high-speed gait of most cursorial quadrupeds. To gallop, an animal must generate ballistic trajectories with characteristic strong impacts, coordinate leg movements with asymmetric footfall phasing, and effectively use compliant members, all the while maintaining dynamic stability. In this paper we seek to further understand the primary biological features necessary for galloping by building and testing a robotic quadruped similar in size to a large goat or antelope. These features include high-speed actuation, energy storage, on-line learning control, and high-performance attitude sensing. Because body dynamics are primarily influenced by the impulses delivered by the legs, the successful design and control of single leg energetics is a major focus of this work. The leg stores energy during flight by adding tension to a spring acting across an articulated knee. During stance, the spring energy is quickly released using a novel capstan design. As a precursor to quadruped control, two intelligent strategies have been developed for verification on a one-legged system. The Levenberg-Marquardt on-line learning method is applied to a simple heuristic controller and provides good control over height and forward velocity. Direct adaptive fuzzy control, which requires no system modeling but is more computationally expensive, exhibits better response. Using these techniques we have been successful in operating one leg at speeds necessary for a dynamic gallop of a machine of this scale. Another necessary component of quadruped locomotion is high-resolution and high-bandwidth attitude sensing. The large ground impact accelerations, which cause problems for any single traditional sensor, are overcome through the use of an inertial sensing approach using updates from optical sensors and vehicle kinematics.

Virtual robot experimentation platform V-REP: a versatile 3D robot simulator

From exploring planets to cleaning homes, the reach and versatility of robotics is vast. The integration of actuation, sensing and control makes robotics systems powerful, but complicates their simulation. This paper introduces a modular and decentralized architecture for robotics simulation. In contrast to centralized approaches, this balances functionality, provides more diversity, and simplifies connectivity between (independent) calculation modules. As the Virtual Robot Experimentation Platform (V-REP) demonstrates, this gives a smallfootprint 3D robot simulator that concurrently simulates control, actuation, sensing and monitoring. Its distributed and modular approach are ideal for complex scenarios in which a diversity of sensors and actuators operate asynchronously with various rates and characteristics. This allows for versatile prototyping applications including systems verification, safety/remote monitoring, rapid algorithm development, and factory automation simulation.

A Pipeline for the Segmentation and Classification of 3D Point Clouds

This paper presents algorithms for fast segmentation of 3D point clouds and subsequent classification of the obtained 3D segments. The method jointly determines the ground surface and segments individual objects in 3D, including overhanging structures. When compared to six other terrain modelling techniques, this approach has minimal error between the sensed data and the representation; and is fast (processing a Velodyne scan in approximately 2 seconds). Applications include improved alignment of successive scans by enabling operations in sections (Velodyne scans are aligned 7% sharper compared to an approach using raw points) and more informed decision-making (paths move around overhangs). The use of segmentation to aid classification through 3D features, such as the Spin Image or the Spherical Harmonic Descriptor, is discussed and experimentally compared. Moreover, the segmentation facilitates a novel approach to 3D classification that bypasses feature extraction and directly compares 3D shapes via the ICP algorithm. This technique is shown to achieve accuracy on par with the best feature based classifier (92.1%) while being significantly faster and allowing a clearer understanding of the classifier’s behaviour.

Immunology-directed methods for distributed robotics: a novel immunity-based architecture for robust control and coordination

This paper presents a novel algorithmic architecture for the coordination and control of large scale distributed robot teams derived from the constructs found within the human immune system. Using this as a guide, the Immunology-derived Distributed Autonomous Robotics Architecture (IDARA) distributes tasks so that broad, all-purpose actions are refined and followed by specific and mediated responses based on each units utility and capability to timely address the systems perceived need(s). This method improves on initial developments in this area by including often overlooked interactions of the innate immune system resulting in a stronger first-order, general response mechanism. This allows for rapid reactions in dynamic environments, especially those lacking significant a priori information. As characterized via computer simulation of a of a self-healing mobile minefield having up to 7,500 mines and 2,750 robots, IDARA provides an efficient, communications light, and scalable architecture that yields significant operation and performance improvements for large-scale multi-robot coordination and control.

Learning navigational maps by observing human motion patterns

Observing human motion patterns is informative for social robots that share the environment with people. This paper presents a methodology to allow a robot to navigate in a complex environment by observing pedestrian positional traces. A continuous probabilistic function is determined using Gaussian process learning and used to infer the direction a robot should take in different parts of the environment. The approach learns and filters noise in the data producing a smooth underlying function that yields more natural movements. Our method combines prior conventional planning strategies with most probable trajectories followed by people in a principled statistical manner, and adapts itself online as more observations become available. The use of learning methods are automatic and require minimal tuning as compared to potential fields or spline function regression. This approach is demonstrated testing in cluttered office and open forum environments using laser and vision sensing modalities. It yields paths that are similar to the expected human behaviour without any a priori knowledge of the environment or explicit programming.

Attitude Estimation for Dynamic Legged Locomotion Using Range and Inertial Sensors

Legged robots offer exceptional mobility in uncharted terrains. Their dynamic nature yields unrivaled mobility, but serves to destabilize the motion estimation process that underlies legged operations. In particular, the discontinuous foot fall patterns and flight phases result in severe impulses, which, in turn, result in excessive accumulation of drift by inertial sensors. Ground range measurements, amongst several others, are robust to this drift yet are limited in application due to their low-bandwidth and sensitivity to ground conditions. In considering the attitude estimation problem for this dynamic legged locomotion, this paper develops a pose calculation method based on ground range measurements. This is used in conjunction with a hybrid Extended Kalman Filter that takes advantage of the ballistic nature of the flight phases. Results indicate that this combination provides rapid, robust estimates of attitude necessary for extended dynamic legged operations. In single leg experiments, which were conducted using low-cost sensing hardware, this method had an RMS error of < 1 °, half that of a non-hybrid EKF approach.

Hybrid elevation maps: 3D surface models for segmentation

This paper presents an algorithm for segmenting 3D point clouds. It extends terrain elevation models by incorporating two types of representations: (1) ground representations based on averaging the height in the point cloud, (2) object models based on a voxelisation of the point cloud. The approach is deployed on Riegl data (dense 3D laser data) acquired in a campus type of environment and compared against six other terrain models. Amongst elevation models, it is shown to provide the best fit to the data as well as being unique in the sense that it jointly performs ground extraction, overhang representation and 3D segmentation. We experimentally demonstrate that the resulting model is also applicable to path planning.

Using Lie group symmetries for fast corrective motion planning

In this paper we develop an algorithmic framework allowing for fast and elegant path correction exploiting Lie group symmetries and operating without the need for explicit control strategies such as cross-track regulation. These systems occur across the gamut of robotics, notably in locomotion, be it ground, underwater, airborne, or surgical domains. Instead of reintegrating an entire trajectory, the method selectively alters small key segments of an initial trajectory in a consistent way so as to transform it via symmetry operations. The algorithm is formulated for arbitrary Lie groups and applied in the context of the special Euclidean group and subgroups thereof. A sampling-based motion planner is developed that uses this method to create paths for underactuated systems with differential constraints. It is also shown how the path correction method acts as a controller within a feedback control loop for real-time path correction. These approaches are demonstrated for ground vehicles in the plane and for flexible bevel tip needle steering in space. The results show that using symmetry-based path correction for motion planning provides a prudent and simple, yet computationally tractable, integrated planning and control strategy.

Design and evaluation of an integrated planar localization method for desktop robotics

Localization and measurement of displacement are critical aspects to the operation and control of mobile robots. The motion of desktop robots, a class of mobile robots designed for use on a table, can be considered a special case of the general localization problem since the vehicle is primarily operated over a flat surface. Using the assumption that the motion of a desktop robot is essentially planar, this paper presents a novel method that senses the motion of two points to obtain both the position and orientation of the robot in two-dimensional space. The paper details how this method can be implemented using low-cost, off-the-shelf sensor hardware components and demonstrates its application in the Desktop-Bot, a compact desktop robot. Experimental testing validated features of this planar localization such as: estimation with minimal mean error (or drift), no external sensing hardware apparatus (i.e., on-board sensing), fast-update rates (/spl sim/50 Hz) and robustness to external occlusion.