Path planning under 2D map is a key issue in robot applications. However, most related algorithms rely on point-by-point traversal. This causes them usually cannot find the strict shortest path, and their time cost increases dramatically as the map scale increases. So we proposed RimJump to solve the above problem, and it is a new path planning method that generates the strict shortest path for a 2D map. RimJump selects points on the edge of barriers to form the strict shortest path. Simulation and experimentation prove that RimJump meets the expected requirements.

In this article, a two-dimensional analysis of biped robot sliding dynamics is performed. First, the dynamics of a biped robot based on feet-slip are derived using the coulomb friction model. The state transition can be formulated in the centroid acceleration space whose diagram is defined as a “triangle of sliding friction” (TSF). The TSF's characteristics are explained by focusing on comparison with the cone of friction which has a similar state decision diagram. Next, for the behavioral simulation of a concrete model, a 2-DOF biped robot is used to analyze the sliding features in terms of the asymmetry of the dynamics of each leg. Finally, the sliding characteristics are applied to the two tasks of running and somersaulting. The results show the robot takes short rapid repetitive steps for running based on frictional asymmetry and theoretically based on torque asymmetry can make one revolution using the large angular momentum acquired during sliding motion.

This paper proposes an alternative environment mapping method for accurate robotic navigation based on 3D information. Typical techniques for 3D mapping using occupancy grid require intensive computational workloads in order to both build and store the map. This work introduces an Occupancy-Elevation Grid (OEG) mapping technique, which is a discrete mapping approach where each cell represents the occupancy probability, the height of the terrain and its variance. This representation allows a mobile robot to know with an accurate degree of certainty whether a place in the environment is occupied by an obstacle and the height of such obstacle. Thus, based on its hardware characteristics, it can make calculations to decide if it is possible to traverse that specific place. In general, the map representation introduced can be used in conjunction with any kind of distance sensor. In this work, we use laser range data and stereo system data with a probabilistic treatment. The resulting maps allow the execution of tasks as decision making for autonomous navigation, exploration, localization and path planning, considering the existence and the height of the obstacles. Experiments carried out with real data demonstrate that the proposed approach yields useful maps for autonomous navigation.

The paper considers the problem of motion planning and posture control of multiple n-link doubly nonholonomic mobile manipulators in an obstacle-cluttered and bounded workspace. The workspace is constrained with the existence of an arbitrary number of fixed obstacles (disks, rods and curves), artificial obstacles and moving obstacles. The coordination of multiple n-link doubly nonholonomic mobile manipulators subjected to such constraints becomes therefore a challenging navigational and steering problem that few papers have considered in the past. Our approach to developing the controllers, which are novel decentralized nonlinear acceleration controllers, is based on a Lyapunov control scheme that is not only intuitively understandable but also allows simple but rigorous development of the controllers. Via the scheme, we showed that the avoidance of all types of obstacles was possible, that the manipulators could reach a neighborhood of their goal and that their final orientation approximated the desired orientation. Computer simulations illustrate these results.

Changes in world-wide population trends have provided new demands for new technologies in areas such as care and rehabilitation. Recent developments in the the field of robotics for neurorehabilitation have shown a range of evidence regarding usefulness of these technologies as a tool to augment traditional physiotherapy. Part of the appeal for these technologies is the possibility to place a rehabilitative tool in one's home, providing a chance for more frequent and accessible technologies for empowering individuals to be in charge of their therapy.

Objective: this manuscript introduces the Supervised Care and Rehabilitation Involving Personal Tele-robotics (SCRIPT) project. The main goal is to demonstrate design and development steps involved in a complex intervention, while examining feasibility of using an instrumented orthotic device for home-based rehabilitation after stroke.

Methods: the project uses a user-centred design methodology to develop a hand/wrist rehabilitation device for home-based therapy after stroke. The patient benefits from a dedicated user interface that allows them to receive feedback on exercise as well as communicating with the health-care professional. The health-care professional is able to use a dedicated interface to send/receive communications and remote-manage patient's exercise routine using provided performance benchmarks. Patients were involved in a feasibility study (n=23) and were instructed to use the device and its interactive games for 180 min per week, around 30 min per day, for a period of 6 weeks, with a 2-months follow up. At the time of this study, only 12 of these patients have finished their 6 weeks trial plus 2 months follow up evaluation.

Results: with the “use feasibility” as objective, our results indicate 2 patients dropping out due to technical difficulty or lack of personal interests to continue. Our frequency of use results indicate that on average, patients used the SCRIPT1 device around 14 min of self-administered therapy a day. The group average for the system usability scale was around 69% supporting system usability.

Conclusions: based on the preliminary results, it is evident that stroke patients were able to use the system in their homes. An average of 14 min a day engagement mediated via three interactive games is promising, given the chronic stage of stroke. During the 2nd year of the project, 6 additional games with more functional relevance in their interaction have been designed to allow for a more variant context for interaction with the system, thus hoping to positively influence the exercise duration. The system usability was tested and provided supporting evidence for this parameter. Additional improvements to the system are planned based on formative feedback throughout the project and during the evaluations. These include a new orthosis that allows a more active control of the amount of assistance and resistance provided, thus aiming to provide a more challenging interaction.

This paper formulates a new scalable algorithm for motion planning and control of multiple point-mass robots. These autonomous robots are designated to move safely to their goals in a priori known workspace cluttered with fixed and moving obstacles of arbitrary positions and sizes. The control laws proposed for obstacle and collision avoidance and target convergence ensure that the equilibrium point of the given system is asymptotically stable. Computer simulations with the proposed technique and applications to a team of two planar (RP) manipulators working together in a common workspace are presented. Also, the robustness of the system in the presence of noise is verified through simulations.

This paper proposes an analytical method of solving the inverse kinematic problem for a humanoid manipulator with five degrees-of-freedom (DOF) under the condition that the target orientation of the manipulator's end-effector is not constrained around an axis fixed with respect to the environment. Since the number of the joints is less than six, the inverse kinematic problem cannot be solved for arbitrarily specified position and orientation of the end-effector. To cope with the problem, a generalized unconstrained orientation is introduced in this paper. In addition, this paper conducts the singularity analysis to identify all singular conditions.

This paper tackles the problem of motion planning and control of a car-like robot in an obstacle-ridden workspace. A kinematic model of the vehicle, governed by a homogeneous system of first-order differential equations, is used. A solution to the multi-tasking problem of target convergence, obstacle avoidance, and posture control is then proposed. The approach of solving the problem is two-fold. Firstly, a novel velocity algorithm is proposed to drive the car-like robot from its initial position to the target position. Secondly, a single layer artificial neural network is trained to avoid disc-shaped obstacles and provide corresponding weights, which are then used to develop a function for the steering angles. Thus, our method does not need a priori knowledge of the environment except for the goal position. With the help of the Direct Method of Lyapunov, it is shown that the proposed forms of the velocity and steering angle ensure point stability. For posture stability, we model the two parallel boundaries of a row-structured parking bay as continua of disk-shaped obstacles. Thus, our method is extendable to ensuring posture stability, which gives the desired final orientation. Computer simulations of the generated path are presented to illustrate the effectiveness of the method.

This paper proposes a robot navigation scheme using wireless visual sensors deployed in an environment. Different from the conventional autonomous robot approaches, the scheme intends to relieve massive on-board information processing required by a robot to its environment so that a robot or a vehicle with less intelligence can exhibit sophisticated mobility. A three-state snake mechanism is developed for coordinating a series of sensors to form a reference path. Wireless visual sensors communicate internal forces with each other along the reference snake for dynamic adjustment, react to repulsive forces from obstacles, and activate a state change in the snake body from a flexible state to a rigid or even to a broken state due to kinematic or environmental constraints. A control snake is further proposed as a tracker of the reference path, taking into account the robot's non-holonomic constraint and limited steering power. A predictive control algorithm is developed to have an optimal velocity profile under robot dynamic constraints for the snake tracking. They together form a unified solution for robot navigation by distributed sensors to deal with the kinematic and dynamic constraints of a robot and to react to dynamic changes in advance. Simulations and experiments demonstrate the capability of a wireless sensor network to carry out low-level control activities for a vehicle.