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Creators/Authors contains: "Mazumdar, Anirban"

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  1. Abstract Series elastic actuators (SEAs) are increasingly popular in wearable robotics due to their high fidelity closed-loop torque control capability. Therefore, it has become increasingly important to characterize its performance when used in dynamic environments. However, the conventional design approach does not fully capture the complexity of the entire exoskeleton system. These limitations stem from identifying design criteria with inadequate biomechanics data, utilizing an off-the-shelf user interface, and applying a benchtop-based proportional-integral-derivative control for actual low-level torque tracking. While this approach shows decent actuator performance, it does not consider human factors such as the dynamic back-driving nature of human-exoskeleton systems as well as soft human tissue dampening during the load transfer. Using holistic design guidelines to improve the SEA-based exoskeleton performance during dynamic locomotion, our final system has an overall mass of 4.8 kg (SEA mass of 1.1 kg) and can provide a peak joint torque of 108 Nm with a maximum velocity of 5.2 rad/s. Additionally, we present a user state-based feedforward controller to further improve the low-level torque tracking for diverse walking conditions. Our study results provide future exoskeleton designers with a foundation to further improve SEA-based exoskeleton’s torque tracking response for maximizing human-exoskeleton performance during dynamic locomotion.
    Free, publicly-accessible full text available April 1, 2024
  2. Abstract In this study, we developed an offline, hierarchical intent recognition system for inferring the timing and direction of motion intent of a human operator when operating in an unstructured environment. There has been an increasing demand for robot agents to assist in these dynamic, rapid motions that are constantly evolving and require quick, accurate estimation of a user’s direction of travel. An experiment was conducted in a motion capture space with six subjects performing threat evasion in eight directions, and their mechanical and neuromuscular signals were recorded for use in our intent recognition system (XGBoost). Investigated against current, analytical methods, our system demonstrated superior performance with quicker direction of travel estimation occurring 140 ms earlier in the movement and a 11.6 deg reduction of error. The results showed that we could also predict the start of the movement 100 ms prior to the actual, thus allowing any physical systems to start up. Our direction estimation had an optimal performance of 8.8 deg, or 2.4% of the 360 deg range of travel, using three-axis kinetic data. The performance of other sensors and their combinations indicate that there are additional possibilities to obtain low estimation error. These findings are promising asmore »they can be used to inform the design of a wearable robot aimed at assisting users in dynamic motions, while in environments with oncoming threats.« less
  3. This paper presents a novel physical gripping framework intended for controlled, high force density attachment on a range of surfaces. Our framework utilizes a light-activated chemical adhesive to attach to surfaces. The cured adhesive is part of a "sacrificial layer," which is shed when the gripper separates from the surface. In order to control adhesive behavior we utilize ultraviolet (UV) light sensitive acrylics which are capable of rapid curing when activated with 380nm light. Once cured, zero input power is needed to hold load. Thin plastic parts can be used as the sacrificial layers, and these can be released using an electric motor. This new gripping framework including the curing load capacity, adhesive deposition, and sacrificial methods are described in detail. Two proof-of concept prototypes are designed, built, and tested. The experimental results illustrate the response time (15-75s depending on load), high holding force-to-weight ratio (10-30), and robustness to material type. Additionally, two drawbacks of this design are discussed: corruption of the gripped surface and a limited number of layers.
  4. Robotic grasping can enable mobile vehicles to physically interact with the environment for delivery, repositioning, or landing. However, the requirements for grippers on mobile vehicles differ substantially from those used for conventional manipulation. Specifically, grippers for dynamic mobile robots should be capable of rapid activation, high force density, low power consumption, and minimal computation. In this work, we present a biologically-inspired robotic gripper designed specifically for mobile platforms. This design exploits a bistable shell to achieve “reflexive” activation based on contact with the environment. The mechanism can close its grasp within 0. 12s without any sensing or control. Electrical input power is not required for grasping or holding load. The reflexive gripper utilizes a novel pneumatic design to open its grasp with low power, and the gripper can carry slung loads up to 28 times its weight. This new mechanism, including the kinematics, static behavior, control structure, and fabrication, is described in detail. A proof of concept prototype is designed, built, and tested. Experimental results are used to characterize performance and demonstrate the potential of these methods.