Jesús Morales

Approximating Kinematics for Tracked Mobile Robots

In this paper we propose a kinematic approach for tracked mobile robots in order to improve motion control and pose estimation. Complex dynamics due to slippage and track–soil interactions make it difficult to predict the exact motion of the vehicle on the basis of track velocities. Nevertheless, real-time computations for autonomous navigation require an effective kinematics approximation without introducing dynamics in the loop. The proposed solution is based on the fact that the instantaneous centers of rotation (ICRs) of treads on the motion plane with respect to the vehicle are dynamics-dependent, but they lie within a bounded area. Thus, optimizing constant ICR positions for a particular terrain results in an approximate kinematic model for tracked mobile robots. Two different approaches are presented for off-line estimation of kinematic parameters: (i) simulation of the stationary response of the dynamic model for the whole velocity range of the vehicle; (ii) introduction of an experimental setup so that a genetic algorithm can produce the model from actual sensor readings. These methods have been evaluated for on-line odometric computations and low-level motion control with the Auriga-α mobile robot on a hard-surface flat soil at moderate speeds.

Experimental kinematics for wheeled skid-steer mobile robots

This work aims at improving real-time motion control and dead-reckoning of wheeled skid-steer vehicles by considering the effects of slippage, but without introducing the complexity of dynamics computations in the loop. This traction scheme is found both in many off-the-shelf mobile robots due to its mechanical simplicity and in outdoor applications due to its maneuverability. In previous works, we reported a method to experimentally obtain an optimized kinematic model for skid-steer tracked vehicles based on the boundedness of the instantaneous centers of rotation (ICRs) of treads on the motion plane. This paper provides further insight on this method, which is now proposed for wheeled skid-steer vehicles. It has been successfully applied to a popular research robotic platform, pioneer P3-AT, with different kinds of tires and terrain types.

Mobile robot motion estimation by 2D scan matching with genetic and iterative closest point algorithms

The paper reports on mobile robot motion estimation based on matching points from successive two-dimensional (2D) laser scans. This ego-motion approach is well suited to unstructured and dynamic environments because it directly uses raw laser points rather than extracted features. We have analyzed the application of two methods that are very different in essence: (i) A 2D version of iterative closest point (ICP), which is widely used for surface registration; (ii) a genetic algorithm (GA), which is a novel approach for this kind of problem. Their performance in terms of real-time applicability and accuracy has been compared in outdoor experiments with nonstop motion under diverse realistic navigation conditions. Based on this analysis, we propose a hybrid GA-ICP algorithm that combines the best characteristics of these pure methods. The experiments have been carried out with the tracked mobile robot Auriga-α and an on-board 2D laser scanner.

Pure-pursuit reactive path tracking for nonholonomic mobile robots with a 2D laser scanner

Due to its simplicity and efficiency, the pure-pursuit path tracking method has been widely employed for planned navigation of nonholonomic ground vehicles. In this paper, we investigate the application of this technique for reactive tracking of paths that are implicitly defined by perceived environmental features. Goal points are obtained through an efficient interpretation of range data from an onboard 2D laser scanner to follow persons, corridors, and walls. Moreover, this formulation allows that a robotic mission can be composed of a combination of different types of path segments. These techniques have been successfully tested in the tracked mobile robot Auriga- in an indoor environment.

Steering Limitations for a Vehicle Pulling Passive Trailers

Motion control of articulated vehicles composed of a nonholonomic tractor and several passive trailers is a difficult underactuated problem. This paper proposes the application of steering limitations to the tractor to avoid inter unit collision during forward motion. This method can be used for systems that combine any type of on-axle and off-axle joints. We propose an algorithm to compute curvature bounds based on the analysis of steady and transient responses. These limitations can be introduced at the path tracking and path planning levels for autonomous navigation. Thus, the tractor can be controlled to follow admissible paths much in the same way as when it does not tow any trailer. The method has been validated experimentally with an off-axle two-trailer setup attached to the tracked mobile robot Auriga-alpha.

Power Consumption Modeling of Skid-Steer Tracked Mobile Robots on Rigid Terrain

Power consumption is a key element in outdoor mobile robot autonomy. This issue is very relevant in skid-steer tracked vehicles on account of their large ground contact area. In this paper, the power losses due to dynamic friction have been modeled from two different perspectives: 1) the power drawn by the rigid terrain and 2) the power supplied by the motors. Comparison of both approaches has provided new insight on skid steering on hard flat terrains at walking speeds. Experimental power models, which also include traction resistance and other power losses, have been obtained for two different track widths over marble flooring and asphalt with Auriga- beta, which is a full-size mobile robot. To this end, various internal probes have been set at different points of the power stream. Furthermore, new energy implications for navigation of these kinds of vehicles have been deduced and tested.

Driver assistance system for backward maneuvers in passive multi-trailer vehicles

Drivers of vehicles with one or several passive trailers, like truck-and-trailer or articulated luggage carriers, have difficulties in backward maneuvers due to jackknife and lack of visibility. Advanced driver assistance systems (ADAS) can be helpful to improve both safety and driver comfort in these complex operations. In this paper, we propose an ADAS that adopts our curvature limitation method for backward multi-trailer vehicles, where the last trailer is considered a virtual tractor and steering limits are established to avoid jackknife and inter-unit collisions. In the proposed solution, when the driver puts the vehicle in reverse, the steering wheel and pedals can be used as if the vehicle was driven from the back of the last trailer with visual feedback from a camera. This system can be implemented in drive-by-wire vehicles, where the steering-wheel feedback force can be customized for the curvature limitation of a given combination of one or several trailers. The system has been tested to tele-operate a mobile robot with two off-axle trailers.

Development of ALACRANE: A Mobile Robotic Assistance for Exploration and Rescue Missions

The paper presents ALACRANE, a new mobile robot assistant for exploration and rescue missions with dexterous load manipulation capability. ALACRANE consists of a tracked vehicle with a 4-DOF articulated arm, whose end-effector is an independent pair of 3-DOF manipulators (LR-Arms) plus a common rotation on the main arm wrist. All actuators are hydraulic in order to provide a high power-to-size ratio for both traction and manipulation. The system is equipped with CCD and IR cameras and a 3D-laser scanner for victim detection and environment perception. Three operation modes have been envisaged for the robot: navigation, main arm positioning, and LR-Arms operation. The control architecture provides different levels of autonomy and tele-operation for each mode. Preliminary tests with the actual system are presented.

Fast range-independent spherical subsampling of 3D laser scanner points and data reduction performance evaluation for scene registration

Three-dimensional laser range-finders are increasingly being incorporated into applications, such as mobile robotics, that require real-time registration of scene data. However, the computational costs of adaptive range-dependent data selection and point cloud matching grow significantly with the number of points. Therefore, fast range-independent subsampling by uniform or random data reduction is usually performed at a preprocessing step. The paper proposes a new range-independent subsampling algorithm that is more effective for the widely used spherical scanning mechanism. As this type of device measures the ranges by composition of two rotations, it samples certain directions with a higher density, which can distort the registration optimization process. The proposed solution uses sensor characteristics to equalize the measure-direction density of the reduced point cloud. The paper also addresses performance assessment of subsampling methods by contributing three benchmark criteria that do not rely on a particular registration technique: one considers the ground truth transformation between two scans, and the other two are based on the analysis of a single scan. The advantages of spherical subsampling are analyzed through a comparison of range-independent methods and a simple range-dependent one with real scans from three representative scenes (urban, natural, and indoors).

Automation of the Arm-Aided Climbing Maneuver for Tracked Mobile Manipulators

Surmounting terrain elevations, such as terraces, is useful to increase the reach of mobile robots operating in disaster areas, construction sites, and natural environments. This paper proposes an autonomous climbing maneuver for tracked mobile manipulators with the help of the onboard arm. The solution includes a fast 3-D scan processing method to estimate a simple set of geometric features for the ascent: three lines that correspond to the low and high edges, and the maximum inclination axis. Furthermore, terraces are classified depending on whether they are reachable through a slope or an abrupt step. In the proposed maneuver, the arm is employed both for shifting the center of gravity of the robot and as an extra limb that can be pushed against the ground. Feedback during climbing can be obtained through an inertial measurement unit, joint absolute encoders, and pressure sensors. Experimental results are presented for terraces of both kinds on rough terrain with the hydraulic mobile manipulator Alacrane.