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The aim of this paper is to introduce a hexapod walking robot specifically designed for applications in humanitarian demining, intended to operate autonomously for several hours. To this end, the paper presents an experimental study for the evaluation of its energy efficiency.

First, the interest of using a walking robot for detection and localization of anti-personnel landmines is described, followed by the description of the mechanical system and the control architecture of the hexapod robot. Second, the energy efficiency of the hexapod robot is assessed to demonstrate its autonomy for performing humanitarian demining tasks. To achieve this, the power consumed by the robot is measured and logged, with a number of different payloads placed on-board (always including the scanning manipulator arm assembled on the robot front end), during the execution of a discontinuous gait on flat terrain.

The hexapod walking robot has demonstrated low energy consumption when it is carrying out several locomotion cycles with different loads on it, which is fundamental to have a desired autonomy. It should be considered that the robot has a mass of about 250 kg and that it has been loaded with additional masses of up to 170 kg during the experiments, with a consumption of mean power of 72 W, approximately.

This work provides insight on the use of a walking robot for humanitarian demining tasks, which has high stability and an autonomy of about 3 hours for a robot with high mass and high payload. In addition, the robot can be supervised and controlled remotely, which is an added value when it is working in the field.

The purpose of this paper is specifically to provide a more intelligent locomotion planning method for a hexapod robot based on trajectory optimization, which could reduce the complexity of locomotion design, shorten time of design and generate efficient and accurate motion.

The authors generated locomotion for the hexapod robot based on trajectory optimization method and it just need to specify the high-level motion requirements. Here the authors first transcribed the trajectory optimization problem to a nonlinear programming problem, in which the specified motion requirements and the dynamics with complementarity constraints were defined as the constraints, then a nonlinear solver was used to solve. The leg compliance was taken into consideration and the generated motions were deployed on the hexapod robot prototype to prove the utility of the method and, meanwhile, the influence of different environments was considered.

The generated motions were deployed on the hexapod robot and the movements were demonstrated very much in line with the planning. The new planning method does not require lots of parameter-tuning work and therefore significantly reduces the cycle for designing a new locomotion.

A locomotion generation method based on trajectory optimization was constructed for a 12-degree of freedom hexapod robot. The variable stiffness compliance of legs was considered to improve the accuracy of locomotion generation. And also, different from some simulation work before, the authors have designed the locomotion in three cases and constructed field tests to demonstrate its utility.

This paper aims to use the Matsuoka’s neural oscillators as the basic units of central pattern generator (CPG), and to offer a new CPG architecture consisting of a dual neural CPG of circular three links responsible for oscillator phase adjustment, to which an external neural oscillator is added, which is responsible for oscillator amplitude adjustment, to control foot depth to balance itself when treading on an obstacle.

It is equipped with a triaxial accelerometer and a triaxial gyroscope to obtain a real-time robot attitude, and to disintegrate the foot tilt in each direction as feedback signals to CPG to restore the robot’ horizontal attitude on an uneven terrain. The CPG controller is a distributed control method, with each foot controller consisting of a group of reciprocally coupling neural oscillators and sensors to generate different locomotion by different coupling patterns.

The experiment results indicated that the gait design method succeeded in enabling a steady hexapod walking on a rugged terrain, the mode of response is such that adjustments can only be made when the tilt occurs.

The overall control mechanism uses individual foot tilts as the feedback signal input to the neural oscillators to change the amplitude and compare against the reference oscillators of fixed amplitude to generate the foot height reference signals that can balance the body, and then convert the control signals, through a trajectory generator, to foot trajectories from which the actual rotation angle of servo motors can be obtained through inverse kinematics to achieve the effect of restoring the balance when traveling.

The controller design based on the bionic CPG model has the ability to restore its balance when its body tilts. In addition to the model’s ability to control locomotion, from the response waveforms of this experiment, it can also be noticed that it can control the foot depth to balance itself when treading on an obstacle, and it can adapt to a changing environment. When the obstacle is removed, the robot can quickly regain its balance.

The purpose of this study is to test a chassis robot on rugged road cargo handling.

Attitude solution of D-H series robot gyroscope speed and acceleration sensor.

In identical experimental environments, hexapodal robots experience smaller deviations when using a four-footed propulsive gait from a typical three-footed gait for forward motion; for the same distance but at different speeds, the deviation basically keeps itself within the same range when the robot advances forward with four-foot propulsive gait; because the foot slide in the three-footed gait sometimes experiences frictions, the robot exhibits a large gap in directional deviations in different courses during motion; for motion using a four-footed propulsive gait, there are minor directional deviations of hexapodal robots resulting from experimental errors, which can be reduced through optimizing mechanical structures.

Planning different gaits can solve problems existing in some typical gaits. This article has put forward a gait planning method for hexapodal robots moving forward with diverse gaits as a redundant multifreedom structure. Subsequent research can combine a multiparallel-legged structure to analyze kinematics, optimize the robot’s mechanical structure and carry out in-depth research of hexapod robot gaits.

At present, more than 100 million undetonated landmines left over from wars remain buried worldwide. These mines kill or injure approximately 3,000 individuals each year (80 persons per day), most of them civilians. They represent a particularly acute problem in developing countries and nations already economically hard hit by war. The problem of unexploded mines has become a serious international issue, with many people striving to find a solution. The purpose of this paper is to examine the requirements of the robotic systems for humanitarian demining purposes. It will discuss a hexapod walking robot developed at the Royal Military Academy of Brussels in collaboration with the Free University of Brussels, Belgium, in the framework of the Humanitarian Demining Project (HUDEM).

Considerations for the design of the walking robot according to the humanitarian demining requirements are discussed in detail.

A successful walking robot design for demining purposes must consider functional requirements relevant to this difficult application. The principal requirements are mentioned in this paper.

This paper is the result of the research of the HUDEM project team and it is of value to engineers and researchers developing robotic systems for humanitarian demining purposes.

This paper aims to evaluate four different simultaneous localization and mapping (SLAM) systems in the context of localization of multi-legged walking robots equipped with compact RGB-D sensors. This paper identifies problems related to in-motion data acquisition in a legged robot and evaluates the particular building blocks and concepts applied in contemporary SLAM systems against these problems. The SLAM systems are evaluated on two independent experimental set-ups, applying a well-established methodology and performance metrics.

Four feature-based SLAM architectures are evaluated with respect to their suitability for localization of multi-legged walking robots. The evaluation methodology is based on the computation of the absolute trajectory error (ATE) and relative pose error (RPE), which are performance metrics well-established in the robotics community. Four sequences of RGB-D frames acquired in two independent experiments using two different six-legged walking robots are used in the evaluation process.

The experiments revealed that the predominant problem characteristics of the legged robots as platforms for SLAM are the abrupt and unpredictable sensor motions, as well as oscillations and vibrations, which corrupt the images captured in-motion. The tested adaptive gait allowed the evaluated SLAM systems to reconstruct proper trajectories. The bundle adjustment-based SLAM systems produced best results, thanks to the use of a map, which enables to establish a large number of constraints for the estimated trajectory.

The evaluation was performed using indoor mockups of terrain. Experiments in more natural and challenging environments are envisioned as part of future research.

The lack of accurate self-localization methods is considered as one of the most important limitations of walking robots. Thus, the evaluation of the state-of-the-art SLAM methods on legged platforms may be useful for all researchers working on walking robots’ autonomy and their use in various applications, such as search, security, agriculture and mining.

The main contribution lies in the integration of the state-of-the-art SLAM methods on walking robots and their thorough experimental evaluation using a well-established methodology. Moreover, a SLAM system designed especially for RGB-D sensors and real-world applications is presented in details.

The purpose of this paper is to describe a novel application of the recently introduced concept from computer vision to self‐localization of a walking robot in unstructured environments. The technique described in this paper enables a walking robot with a monocular vision system (single camera) to obtain precise estimates of its pose with regard to the six degrees of freedom. This capability is essential in search and rescue missions in collapsed buildings, polluted industrial plants, etc.

The Parallel Tracking and Mapping (PTAM) algorithm and the Inertial Measurement Unit (IMU) are used to determine the 6‐d.o.f. pose of a walking robot. Bundle‐adjustment‐based tracking and structure reconstruction are applied to obtain precise camera poses from the monocular vision data. The inclination of the robot's platform is determined by using IMU. The self‐localization system is used together with the RRT‐based motion planner, which allows to walk autonomously on rough, previously unknown terrain. The presented system operates on‐line on the real hexapod robot. Efficiency and precision of the proposed solution are demonstrated by experimental data.

The PTAM‐based self‐localization system enables the robot to walk autonomously on rough terrain. The software operates on‐line and can be implemented on the robot's on‐board PC. Results of the experiments show that the position error is small enough to allow robust elevation mapping using the laser scanner. In spite of the unavoidable feet slippages, the walking robot which uses PTAM for self‐localization can precisely estimate its position and successfully recover from motion execution errors.

So far the presented self‐localization system was tested in limited‐scale indoor experiments. Experiments with more realistic outdoor scenarios are scheduled as further work.

Precise self‐localization may be one of the most important factors enabling the use of walking robots in practical USAR missions. The results of research on precise self‐localization in 6‐d.o.f. may be also useful for autonomous robots in other application areas: construction, agriculture, military.

The vision‐based self‐localization algorithm used in the presented research is not new, but the contribution lies in its implementation/integration on a walking robot, and experimental evaluation in the demanding problem of precise self‐localization in rough terrain.

The 2003 CLAWAR conference featured 130 papers on topics related to climbing and walking robots. The paper reviews the conference, highlighting the areas of entertainment robots, de‐mining robots, manufacturing applications, the use of artificial pneumatic muscles and robots for volcanic exploration.

The purpose of this paper is to review the current application areas of shape memory alloy (SMA) actuators in intelligent robotic systems and devices.

This paper analyses how actuation and sensing functions of the SMA actuator have been exploited and incorporated in micro and macro robotic devices, developed for medical and non‐medical applications. The speed of response of SMA actuator mostly depends upon its shape and size, addition and removal of heat and the bias force applied. All these factors have impact on the overall size of the robotic device and the degree of freedom (dof) obtained and hence, a comprehensive survey is made highlighting these aspects. Also described are the mechatronic aspects like the software and hardware used in an industrial environment for the control of such nonlinear actuator and the type of sensory feedback devices incorporated for obtaining better control, positioning accuracy and fast response.

SMA actuators find wide applications in various facets of robotic equipments. Selecting a suitable shape, fast heating and cooling method and better intelligent control technique with or without feedback devices could optimize its performance.

The frequency of SMA actuation purely depends on the rate of heat energy added to and removed from the actuator, which in turn depends upon interrelated nonlinear parameters.

For increasing the dof of robots, number of actuators also have to be increased that leads to complex control problems.

Explains the suitability of SMA as actuators in smart robotic systems, possibility of miniaturisation. It also highlights the difficulties faced by the SMA research community.