A planning framework of environment detection for unmanned ground vehicle in unknown off-road environment

This paper describes a planning framework of environment detection for unmanned ground vehicle (UGV) in the completely unknown off-road environment, which is able to quickly guide the UGV with nonholonomic constraints to detect the environmental information as much as possible. The contributions of this paper contain four fold. First, due to the sensor characteristics of camera and lidar, we present a two-layer combined detection map which can accurately represent the detected and undetected area. Second a frontier extraction algorithm based on RRT considering information acquisition and nonholonomic constraints of UGV is used to extract the target pose. Third, we use a search path planning method based on motion primitive which is able to handle obstacle constraints of environment, nonholonomic constraints of UGV. Fourth the heuristic fusion is proposed to guide the extension of motion primitives to generate a kinodynamically feasible and collision-free trajectory in real-time. And it works well in both simulation and real scene.

Research on Discrete Semantics in Continuous Hand Joint Movement Based on Perception and Expression

Continuous movements of the hand contain discrete expressions of meaning, forming a variety of semantic gestures. For example, it is generally considered that the bending of the finger includes three semantic states of bending, half bending, and straightening. However, there is still no research on the number of semantic states that can be conveyed by each movement primitive of the hand, especially the interval of each semantic state and the representative movement angle. To clarify these issues, we conducted experiments of perception and expression. Experiments 1 and 2 focused on perceivable semantic levels and boundaries of different motion primitive units from the perspective of visual semantic perception. Experiment 3 verified and optimized the segmentation results obtained above and further determined the typical motion values of each semantic state. Furthermore, in Experiment 4, the empirical application of the above semantic state segmentation was illustrated by using Leap Motion as an example. We ended up with the discrete gesture semantic expression space both in the real world and Leap Motion Digital World, containing the clearly defined number of semantic states of each hand motion primitive unit and boundaries and typical motion angle values of each state. Construction of this quantitative semantic expression will play a role in guiding and advancing research in the fields of gesture coding, gesture recognition, and gesture design.

Analysis and synthesis of assistive tools for insertion tasks

This article studies two types of assembly tasks, namely snap-fit insertions and press-fit hose insertions. Experimental data and theoretical modelling of a snap-fit assembly are used to design a tool that can perform the snap-fit task effectively. The design process of the tool is presented and experimental tests developed to validate its effectiveness are described. Hose insertion experiments are then performed and the results are analyzed in order to develop strategies for the effective insertion of press-fit components in assembly tasks. A motion primitive strategy is first explored, followed by a vibration oriented strategy. Finally, a video demonstrating the experiments accompanies this paper.

Purcell’s Three-Link Swimmer: Assessment of Geometry and Gaits for Optimal Displacement and Efficiency

This paper studies the displacement and efficiency of a Purcell’s three-link microswimmer in low Reynolds number regime, capable of moving by the implementation of a motion primitive or gait. An optimization is accomplished attending to the geometry of the swimmer and the motion primitives, considering the shape of the gait and its amplitude. The objective is to find the geometry of the swimmer, amplitude and shape of the gaits which make optimal the displacement and efficiency, in both an individual way and combined (the last case will be referred to as multiobjective optimization). Three traditional gaits are compared with two primitives proposed by the authors and other three gaits recently defined in the literature. Results demonstrate that the highest displacement is obtained by the Tam and Hosoi optimal velocity gait, which also achieves the best efficiency in terms of energy consumption. The rectilinear and Tam and Hosoi optimal efficiency gaits are the second optimum primitives. Regarding the multiobjective optimization and considering the two criteria with the same weight, the optimum gaits turn out to be the rectilinear and Tam and Hosoi optimal efficiency gaits. Thus, the conclusions of this study can help designers to select, on the one hand, the best swimmer geometry for a desired motion primitive and, on the other, the optimal method of motion for trajectory tracking for such a kind of Purcell’s swimmers depending on the desired control objective.

Design of Robotic Motion Platform utilising Continuous Contact Skating

The continuous contact-based skating technique utilises the sideways movement of the two skates while changing the orientation of the two skates simultaneously. The skates remain in contact with the surface. A mathematical model mimicking a continuous skating technique is developed to analyse the kinematic behaviour of the platform. Kinematic and dynamic equations of motion are derived for the impending non-holonomic constraints. Heuristic-based motion primitives are defined to steer the robotic platform. For the lateral movement of the platform, a creeping based motion primitive is proposed. A prototype of the robotic platform is developed with three actuated degrees of freedom – orientation of two skates and distance between them. A multibody model of the platform is also developed in MATLAB. Analytical expressions are verified to be useful using the simulation and experimental results. The robotic platform follows the desired motion profiles. However, the initial deviation has been observed in both the simulations and experiments due to the slipping of the roller skate at the contact point with the surface. The platform can be effectively used in a structured environment autonomously.

Motion Primitive Approach to Rotorcraft Regime Recognition

This paper describes a novel approach to regime recognition based on the notion of motion primitives. Originally developed for path planning, motion primitives decompose a vehicle trajectory into maneuver and trim segments. In a regime recognition context, this decomposition can be used to improve component life tracking through separate classification of trim segments and maneuver segments. The proposed algorithm functions in three major steps. The first step consists of classifying the flight data into trim and maneuver segments. The second step leverages the information in the trim state and control vectors to classify each trim segment as a particular trim regime based on conditional logic. The final step makes use of dynamic time warping for the classification of each maneuver segment (flown between two trim segments) as a particular maneuver regime. Accuracy of the proposed algorithm is evaluated using simulated flight data for the SH-60B, and advantages of the proposed method compared to a threshold-based algorithm are assessed. The algorithm is also applied to actual flight data from a generic utility helicopter to demonstrate operation of the algorithm using real-world data.