Surrounding vehicles may misjudge an autonomous vehicle’s intended motion and yield or merge at the wrong time. These conflicts are difficult to test systematically when surrounding vehicles’ expectations cannot be varied separately from the autonomous vehicle’s planned motion. This paper proposes an intention-misjudgment-oriented background-traffic generator for autonomous-vehicle testing. A speed-intention perturbation mechanism separates the nominal speed plan of the vehicle under test (VUT) from the estimate supplied to surrounding vehicles, enabling controlled underestimation and overestimation. A Transformer-based interaction encoder relates the perturbed estimate to traffic context and 50-step guiding-lane references to generate context-dependent responses. Multimodal decoding represents alternative responses, while learned affine state updates couple their evolution to inter-vehicle interactions and VUT control inputs. In highway-merging simulations, the best-matching generated trajectories have lower average and endpoint position errors than those of the Mixtures of Affine Time-varying Systems (MATS) baseline trajectory-prediction model at all three comparison speeds. Across 2353 matched initial scenarios, underestimating the VUT’s future speed by 25% yields an observed collision rate of 11.3%, compared with 6.7% under accurate estimation. The generated cases illustrate conflicts associated with delayed lane changes and altered passing order. These results characterize controlled, simulator-based stress-test outcomes in the IDM–MOBIL highway-merging setting; they do not constitute empirical validation of human-driver responses to intention misjudgment.
Dielectric elastomer actuator (DEA)-driven capsule robots convert periodic excitations into net translation through passive constraints, yet a systematic study on optimal constraint design remains largely unexplored. To address this gap, we present a comparative numerical study of six passive constraint families that range from linear and bistable springs to limit stops and polynomial shapes and encompass 2447 configurations under a reference condition. The best configuration of each family spans more than an order of magnitude in speed, from 2.62 mm/s (linear spring) to 33.86 mm/s (asymmetric bistable). We find that the sign of the constraint-force derivative at the rest position separates every family with negative rest-position stiffness from every family with positive stiffness, whereas the second derivative (curvature) shows no correlation with speed. Building on this observation, we formulate a library-based inverse-design framework that treats velocity as a specification and minimizes the peak driving force. The comparisons reported here are made under one reference condition, and the ranking is therefore a property of the library as sampled rather than a general design rule. For example, relaxing the target velocity from 25 mm/s to 23 mm/s reduces the peak force from 0.31 N to 0.19 N. These results move passive-constraint design from empirical trial-and-error toward a requirement-driven methodology for future soft capsule robots.
Traditional 3-RRS and 3-RPS mechanisms adopt open-chain limbs, where R, P, and S denote revolute, prismatic, and spherical joints, respectively. Although these mechanisms are widely used, they suffer from insufficient stiffness and accuracy under heavy-load and high-precision operating conditions. By contrast, existing configurations equipped with closed-loop sub-chains can offer improved stiffness yet suffer from complex structures. To address these issues, a novel closed-loop actuated 3-(RRRPR)S parallel mechanism is proposed. The configuration consists of a moving platform, a fixed platform, and three identical (RRRPR)S closed-loop actuated limbs. Each limb contains a closed-loop sub-chain composed of a planar five-bar mechanism (RRRPR), in which the prismatic joint P is the actuated joint. The design of the closed-loop actuated limb effectively shortens the transmission chain length of the limb, reduces the overall height of the mechanism, and improves its stiffness and dynamic characteristics. To address the complex constraint relationship imposed by the closed-loop sub-chain (RRRPR) on the moving platform, the equivalent motion screw theory is used to systematically analyze the rationality of the actuated joint selection, thereby ensuring the correctness of the configuration design. Through the analysis of the motion characteristics of the closed-loop sub-chain, the motion mapping relationship between the serial open-chain limb and the closed-loop actuated limb is established. By combining the influence coefficient theory with the Newton–Euler equations in screw form, the kinematic and dynamic models of the mechanism are established in a concise and compact form. A prototype of the 3-(RRRPR)S closed-loop actuated parallel mechanism was developed. Experimental results show that the mechanism can achieve continuous and stable motion under the tested motion groups, providing a practical basis for the engineering application of similar parallel mechanisms.
To address the problems of cable slackness and non-smooth cable-tension variation curves during the motion of an antagonistic cable-driven parallel robot (CDPR), this paper focuses on a three-degree-of-freedom (DOF) redundantly constrained CDPR. First, an inverse kinematics model of the robot is established using the vector closed-loop principle. Second, a dynamics model of the robot is established using the Newton–Euler method. Linear programming, quadratic programming, and nonlinear programming are respectively adopted to optimize the cable tensions. Through numerical simulation and comparative analysis, the nonlinear programming method, which produces the smallest cable tension fluctuations and the smoothest cable tension variation curves, is selected as the optimal approach among the three tested methods. Finally, numerical simulations and experiments verify the correctness of the inverse kinematic and dynamic models of the robot, as well as the effectiveness of the proposed cable tension optimization method. The results provide a theoretical reference for dynamic modeling and cable tension optimization of similar redundantly constrained CDPRs.
Speed ripple attenuation in geared flexible drives requires control of synchronous components and residual fluctuations within an existing embedded control architecture. This paper develops a five-state delay-coordinate predictive damping controller (D5–PD) that adds auxiliary q-axis current to a proportional–integral (PI)-regulated drive. Direction-specific models are identified from drive speed history and auxiliary current records with exact delay shifts. A three-step output-weighted design is solved offline and deployed as five-coefficient feedback with scalar scheduling and current limits, at a 1 ms auxiliary update period on an F28379D. Experiments compare PI, six-branch multi-resonant control (MR), and D5–PD under six conditions with three runs per controller. At +300 r/min and +1 A, D5–PD reduces mean speed ripple root mean square (RMS) by 38.83% relative to PI and 5.61% relative to MR at nearly equal auxiliary command alternating-current (AC) RMS. Its load current-normalized responses at 2 and 8 Hz are 37.39% and 60.17% lower than MR without disturbance-specific retuning. Total ripple is lower than PI in all six conditions and MR in five; residual RMS is lower than MR throughout. A separate 0.20 A benchmark with six records per method gives 2.12% lower total ripple and 7.68% lower command RMS than proportional ripple damping. These results demonstrate an embedded auxiliary damping implementation and characterize its tradeoffs with frequency-selective and proportional feedback in terms of total ripple, residual fluctuations and command demand.
