A robot may include a body and a mobility system. The mobility system may include a multi-link system coupled to the body. The multi-link system may form a kinematic chain to control movement of the multi-link system. The mobility system may include an actuator coupled to a particular link of the multi-link system. The actuator may drive the particular link and move the multi-link system in a single dimension relative to the body for interaction of the robot with a feature.
B60G 17/0165 - Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load the regulating means comprising electric or electronic elements characterised by their responsiveness, when the vehicle is travelling, to specific motion, a specific condition, or driver input to an external condition, e.g. rough road surface, side wind
B60G 3/20 - Resilient suspensions for a single wheel with two or more pivoted arms, e.g. parallelogram all arms being rigid
B60G 11/18 - Resilient suspensions characterised by arrangement, location, or kind of springs having torsion-bar springs only
2.
CONTROL AND TRAINING OF ROBOTS USING LARGE LANGUAGE MODELS
A method may include sending a query to one of a cobot or an LLM, where the query may be formed to trigger the cobot to perform a target objective, and where the LLM may be constrained to respond to requests to cause the cobot to perform a given objective with a set of human-readable discrete tasks to accomplish the given objective. The method may also include receiving a target set of human-readable discrete tasks from the LLM, where the target set of human-readable discrete tasks may correspond to target computer-readable code that is configured to cause the cobot to perform the target objective. The method may additionally include auditing the target set of human-readable discrete tasks, and, based on the target set of human-readable discrete tasks passing the audit, authorizing the cobot to implement the target computer-readable code to perform the target objective.
A robot may include a body, a control system, and a control interface. The control system may be configured to cause the robot to transition between an autonomous mode and an intervention mode. In the autonomous mode, the control system may be configured to autonomously control the body within an environment, In the intervention mode, the control system may be configured to control the body within the environment based on operator input. The control interface may be configured to receive the operator input.
A robot may include a support portion and a conveyor. The conveyor may be coupled to the support portion. The conveyor may include a belt configured to interface with an object to cause the object to be positioned on or positioned off the belt. The conveyor may be configured to move along a height of the support portion to adjust a height of the belt relative to the support portion to permit the object to be positioned on or positioned off the belt at a variety of heights.
A robot may include a body, a control system, and a control interface. The control system may be configured to cause the robot to transition between an autonomous mode and an intervention mode. In the autonomous mode, the control system may be configured to autonomously control the body within an environment, In the intervention mode, the control system may be configured to control the body within the environment based on operator input. The control interface may be configured to receive the operator input.
A robot may include a support portion and a conveyor. The conveyor may be coupled to the support portion. The conveyor may include a belt configured to interface with an object to cause the object to be positioned on or positioned off the belt. The conveyor may be configured to move along a height of the support portion to adjust a height of the belt relative to the support portion to permit the object to be positioned on or positioned off the belt at a variety of heights.
B65G 41/00 - Supporting frames or bases for conveyors as a whole, e.g. transportable conveyor frames
B65G 21/12 - Supporting or protective framework or housings for endless load-carriers or traction elements of belt or chain conveyors movable, or having interchangeable or relatively- movable partsDevices for moving framework or parts thereof to allow adjustment of position of load-carrier or traction element as a whole
B65G 47/90 - Devices for picking-up and depositing articles or materials
B25J 11/00 - Manipulators not otherwise provided for
B25J 5/00 - Manipulators mounted on wheels or on carriages
B25J 5/02 - Manipulators mounted on wheels or on carriages travelling along a guideway
A robot may include a load system including an interface device configured to engage with objects including different features. The robot may include a control system configured to detect a current feature of a current object. The control system may also be configured to cause the load system to be positioned based on the cunent feature of the current object to cause the interface device to engage with the current object.
A robot may include a load system including an interface device configured to engage with objects including different features. The robot may include a control system configured to detect a current feature of a current object. The control system may also be configured to cause the load system to be positioned based on the current feature of the current object to cause the interface device to engage with the current object.
A method may include obtaining an artificial intelligence (AI) model configured to identify series of tasks to be performed by a robot in accordance with general parameters. The method may include obtaining data indicating a particular parameter corresponding to a particular environment. The method may include identifying, using the AI model, the particular parameter as corresponding to the particular environment. The particular parameter may be used by the AI model to identify the series of tasks to be performed by the robot such that the series of tasks are performed in accordance with the general and the particular parameters. The method may include identifying, using the AI model and the particular parameter, a series of tasks to be performed by the robot to complete an operation in the particular environment. The method may include causing the robot to autonomously perform the series of tasks in the particular environment.
A method may include receiving input data identifying an operation to be completed in an environment. The method may also include identifying, using an artificial intelligence (Al) model, a series of tasks to be performed by robots to complete the operation based on the input data. In addition, the method may include identifying a subset of the robots to perform the series of tasks based on capabilities to be used to perform the series of tasks. Further, the method may include causing the subset of the robots to autonomously perform the series of tasks to complete the operation.
A method may include obtaining an artificial intelligence (Al) model configured to identify series of tasks to be performed by a robot in accordance with general parameters. The method may include obtaining data indicating a particular parameter corresponding to a particular environment. The method may include identifying, using the Al model, the particular parameter as corresponding to the particular environment. The particular parameter may be used by the Al model to identify the series of tasks to be performed by the robot such that the series of tasks are performed in accordance with the general and the particular parameters. The method may include identifying, using the Al model and the particular parameter, a series of tasks to be performed by the robot to complete an operation in the particular environment. The method may include causing the robot to autonomously perform the series of tasks in the particular environment.
A method may include receiving input data identifying an operation to be completed in an environment. The method may also include identifying, using an artificial intelligence (AI) model, a series of tasks to be performed by robots to complete the operation based on the input data. In addition, the method may include identifying a subset of the robots to perform the series of tasks based on capabilities to be used to perform the series of tasks. Further, the method may include causing the subset of the robots to autonomously perform the series of tasks to complete the operation.
A method may include obtaining input data corresponding to a robot. The method may also include generating, using an artificial intelligence (Al) model, output data based on the input data. The output data may be representative of a state of the robot. In addition, the method may include identifying, using an Al policy model, a set of tasks to be performed by the robot based on the output data. The set of tasks may involve movement of the robot associated with the state of the robot to perform an operation. The method may include causing the robot to autonomously perform the set of tasks to complete the operation.
One or more embodiments of the present disclosure may include a method. The method may include receiving an instruction identifying an operation to be completed by a robot. The method may also include identifying, using an artificial intelligence (AI) model, a task to be performed by the robot to complete the operation. Additionally, the method may include identifying, using the AI model, a series of movements to be made by the robot to perform the task. Further, the method may include identifying, using the AI model, a series of raw electrical signals configured to cause actuators to move the robot in accordance with the series of movements. The method may include generating the series of raw electrical signals to cause the actuators to move the robot in accordance with the series of movements and cause the robot to perform the task.
A method may include obtaining input data corresponding to a robot. The method may also include generating, using an artificial intelligence (AI) model, output data based on the input data. The output data may be representative of a state of the robot. In addition, the method may include identifying, using an AI policy model, a set of tasks to be performed by the robot based on the output data. The set of tasks may involve movement of the robot associated with the state of the robot to perform an operation. The method may include causing the robot to autonomously perform the set of tasks to complete the operation.
One or more embodiments of the present disclosure may include a method. The method may include receiving an instruction identifying an operation to be completed by a robot. The method may also include identifying, using an artificial intelligence (Al) model, a task to be performed by the robot to complete the operation. Additionally, the method may include identifying, using the Al model, a series of movements to be made by the robot to perform the task. Further, the method may include identifying, using the Al model, a series of raw electrical signals configured to cause actuators to move the robot in accordance with the series of movements. The method may include generating the series of raw electrical signals to cause the actuators to move the robot in accordance with the series of movements and cause the robot to perform the task.
A collaborative robot may include an extension member, a mobility body, a first wheel, a second wheel, and a support mast. The extension member may selectively interface with a load. The first wheel may be operatively coupled to a first side of the mobility body. The second wheel may be operatively coupled to a second side of the mobility body. The first wheel and the second wheel may facilitate movement of the collaborative robot within an environment. The support mast may be operatively coupled to the extension member. The support mast may also be fixedly coupled to the mobility body at a proximal end of the support mast. The support mast may adjust a height of the extension member to facilitate the selective interface of the extension member with the load.
B25J 19/00 - Accessories fitted to manipulators, e.g. for monitoring, for viewingSafety devices combined with or specially adapted for use in connection with manipulators
B62D 57/028 - Vehicles characterised by having other propulsion or other ground-engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members having wheels and mechanical legs
B66F 9/06 - Devices for lifting or lowering bulky or heavy goods for loading or unloading purposes movable, with their loads, on wheels or the like, e.g. fork-lift trucks
A method may include sending a query to one of a cobot or an LLM, where the query may be formed to trigger the cobot to perform a target objective, and where the LLM may be constrained to respond to requests to cause the cobot to perform a given objective with a set of human-readable discrete tasks to accomplish the given objective. The method may also include receiving a target set of human-readable discrete tasks from the LLM, where the target set of human-readable discrete tasks may correspond to target computer-readable code that is configured to cause the cobot to perform the target objective. The method may additionally include auditing the target set of human-readable discrete tasks, and, based on the target set of human-readable discrete tasks passing the audit, authorizing the cobot to implement the target computer-readable code to perform the target objective.
A method may include sending a query to one of a cobot or an ELM. where the query may be formed to trigger the cobot to perform a target objective, and where the ELM may be constrained to respond to requests to cause the cobot to perform a given objective with a set of human-readable discrete tasks to accomplish the given objective. The method may also include receiving a target set of human-readable discrete tasks from the ELM, where the target set of human-readable discrete tasks may correspond to target computer-readable code that is configured to cause the cobot to perform the target objective. The method may additionally include auditing the target set of human-readable discrete tasks, and, based on the target set of human-readable discrete tasks passing the audit, authorizing the cobot to implement the target computer-readable code to perform the target objective.
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