Catálogo de publicaciones - libros

This paper presents a Bayesian approach to the problem of searching for a single lost target by a single autonomous sensor platform. The target may be static or mobile but not evading. Two candidate utility functions for the control solution are highlighted, namely the Mean Time to Detection, and the Cumulative Probability of Detection. The framework is implemented for an airborne vehicle looking for both a stationary and a drifting target at sea. Simulation results for different control solutions are investigated and compared to demonstrate the effectiveness of the method.

This paper presents analysis of traction mechanics and control of a lunar/planetary rover based on the models obtained from terramechanics. A case study has been conducted for a rover test bed to negotiate a slope of loose soil such as regolith that covers most of lunar surface. The tire traction force is modeled as a function of the vertical load and slip ratio of the wheel. Bekker’s terramechanic formulae are employed to derive an improved practical model that calculates net traction force, referred to as Drawbar Pull, with a reasonable precision. Experiments are carried out in two phases. First, the physical behavior of a wheel on loose soil is observed using a single-wheel test bed, then the empirical parameters of the tire and soil are identified. Second, the slope climbing capability is studied by using a rover test bed that has independently driven four wheels. The traction margin and slip margin are defined to be used in a traction control. In the slope experiment, it turned out that the climbing capability was saturated at 14 degrees due to the lack of enough driving torque in wheels. But theoretical investigation suggests that this is not the limitation of terrain trafficability and climbing capability can be improved by increased driving torque and proper load distribution.

Robotic ground vehicles are systems that use gravity and contact forces with the ground to perform motion. In this paper we will focus on n-wheeled vehicles able to perform motion with all the wheels maintaining contact at the same time. The main goal of this work is to establish the implication of the topological architecture of the vehicle mechanism on criteria such as climbing skills, robustness, weight, power consumption, and price. Tools will be provided to help the robot designer to understand the implications of important design parameters like the number of wheels, the vehicle mechanism, and the motorisation of joints on the above criteria. Two examples of innovative locomotion concepts for rough terrain are presented and discussed.

We proposed a new holonomic mobile mechanism which is capable of running over the step. This mechanism realizes omni-directional motion on flat floor and passes over non-flat ground in forward or backward direction. The vehicle equips seven omni-directional wheels with cylindrical free rollers and two passive body axis that provide to change the shape of the body on the rough terrain. This paper presents a method to control the wheels for passing over rough terrain with the stable posture. Our vehicle is required to keep synchronization among its wheels for climbing the step without slipping and blocking. Therefore, in this paper, an algorithm of synchronization among all wheels is proposed. The performance of our system is experimented by means of computer simulations and experiments using our prototype vehicle.

A simple sensor-based walking on rough terrains for legged robots using an acceleration sensor attached to the body is described. The algorithm is implemented to a developed proto-type robot with limb mechanism, which has six limbs that can be used for both locomotion and manipulation. The six limbs are arranged on the body radially to have uniform property in all directions. This symmetrical structure allows the robot to generate a gait trajectory for omnidirectional locomotion in a simple manner. The trajectory of the sensorbased walking is obtained by a small conversion of this simple trajectory. The proto-type robot walks on the uneven ground while adjusting the pose of the body to keep high stability margin. Finally, adequate footholds of supporting limbs are examined for manipulation tasks by two neighboring limbs of the robot.

This paper details the development of a machine learning system which uses the helicopter state and the actions of an instructing pilot to synthesise helicopter control modules online. Aggressive destabilisation/restabilisation sequences are used for training, such that a wide state-space envelope is covered during training. The performance of heading, roll, pitch, height and lateral velocity control learning is presented using our Xcell 60 experimental platform. The helicopter is demonstrated to be stabilised on all axes using the “learning from a pilot” technique. To our knowledge, this is the first time a “learning from a pilot” technique has been successfully applied to all axes.

We present a vision-based algorithm designed to enable an autonomous helicopter to land on a moving target. The helicopter is required to identify the target, track it, and land on it while the target is in motion. We use Hu’s moments of inertia for precise target recognition and a Kalman filter for target tracking. Based on the output of the tracker, a simple trajectory controller is implemented which (within the given constraints) ensures that the helicopter is able to land on the target. We present data collected from manual flights which validate our tracking algorithm.

This paper describes initial results for a laser-based aerial mapping system. Our approach applies a real-time laser scan matching algorithm to 2-D range data acquired by a remotely controlled helicopter. Results obtain for urban and natural terrain exhibit an unprecendented level of spatial detail in the resulting 3-D maps.

Applying low-cost sensors for the Guidance, Navigation and Control (GNC) of an autonomous Uninhibited Aerial Vehicle (UAV) is an extremely challenging area. This paper presents the real-time results of applying a low-cost Inertial Measurement Unit (IMU) and Global Positioning System (GPS) receiver for the GNC. The INS/GPS navigation loop provides continuous and reliable navigation solutions to the guidance and flight control loop for autonomous flight. With additional air data and engine thrust data, the guidance loop computes the guidance demands to follow way-point scenarios. The flight control loop generates actuator signals for the control surfaces and thrust vector. The whole GNC algorithm was implemented within an embedded flight control computer. The real-time flight test results show that the vehicle can perform the autonomous flight reliably even under high maneuvering scenarios.

This paper presents a compact Millimeter Wave (MMW) radar unit that has been developed to be used as a Range, Bearing and Elevation (RBE) sensor on the Brumby Mk III Unmanned Air Vehicles (UAV). The Brumby MkIII is the flight platform used in the Autonomous Navigation and Sensing Experimental Research (ANSER) project which is focused on the development and demonstration of the Decentralised Data Fusion (DDF) and Simultaneous Localisation and Map Building (SLAM) algorithms on multiple UAVs. In the airborne DDF and SLAM demonstrations with UAVs, it is essential to have a terrain sensor on board for the RBE measurements of the ground targets. The focus of this paper is the hardware and software components of the MMW radar as an RBE sensor in the context of the ANSER project.