Artificial multiped and motion controller therefor
OwnerTorsten Reilinventor
Life of this patent
Estimating the term…
Abstract
An artificial multiped is constructed (either in simulation or embodied) in such a way that its natural body dynamics allow the lower part of each leg to swing naturally under the influence of gravity. The upper part of each leg is actively actuated in the sagittal plane. The necessary input to drive the above-mentioned actuators is derived from a neural network controller. The latter is arranged as two bi-directionally coupled chains of neural oscillators, the number of which equals twice that of the legs to be actuated. Parameter optimisation of the controllers is achieved by evolutionary computation in the form of a genetic algorithm.
Claims102
An artificial multiped, comprising:
- a body trunk;
- at least two legs depending from the trunk, each leg having at least a first, upper part and a second, relatively lower part pivotable about the said first upper part;
- a plurality of hip joints each connecting the upper part of an associated leg to the body trunk;
- an actuator arranged to move the upper part of each leg in an arc about the hip joint;
- a neural controller arranged to control the movement of the said actuator such that, as each upper leg part is moved through the said arc, the corresponding lower part thereof is arranged to describe an apparently substantially free-swinging movement over at least a part of the said upper leg part movement.
The multiped of any preceding claim comprising at least one actuator per leg, arranged to actuate the associated hip joint so as to cause the corresponding upper leg part to move.
The multiped of any one of the preceding claims, in which each hip joint has only one degree of freedom such that the corresponding upper leg part is constrained to move only sagitally.
The multiped of any preceding claim, in which each lower leg part is freely pivotable about the upper leg part but wherein the angle between the said upper and lower leg parts is limited in use.
The multiped of any preceding claim, further comprising a plurality of feet each connected to an end of the lower part of a corresponding leg via an ankle joint which acts in use as a damped torsional spring.
The multiped of any preceding claim, in which the neural controller comprises a neural network having a plurality of neurones, at least two of the neurones acting as motor neurones each arranged to control the movement of the actuator so as to cause locomotion of the said trunk via the legs.
The multiped of any preceding claim, comprising two legs and two associated hips such that the multiped is a biped.
A controller for an artificial biped, the biped comprising two legs depending from a trunk and being capable of actuation via an actuator, the controller comprising a neural network having a plurality of neurones, at least two of the neurones acting as motor neurones which are arranged to control the movement of the actuator so as to cause locomotion of the trunk via the legs.
An artificial biped comprising:
- a body trunk;
- two legs depending from the trunk, each leg having a first, upper part and a second, lower part freely pivotable about the said first upper part;
- two hip joints, each one connecting the upper part of an associated one of the two legs to the body trunk;
- a controller, comprising two bi-directionally coupled pairs of identical oscillators embodied as a neural network having a plurality of neurones, at least two neurones acting as motor neurones;
- and
- a force-limited velocity constraint actuator arranged to move the upper part of each leg in an arc about its associated hip joint, and in which the torque, PT, applied to the upper part of each of the two legs is a function of the desired velocity of movement of the upper part of each leg relative to the body trunk, and wherein the desired velocity of movement is related to a difference between the actual and the desired angle between each upper leg part and the body trunk, the desired relative angle being derived from the neural controller;
- the controller being arranged to control the actuation of the actuator such that, as each upper leg part is moved through the said arc, the corresponding lower part thereof describes an apparently substantially free-swinging movement over at least a part of the said upper leg part movement.
A computer system comprising:
- processing means arranged
- (i) to generate an image, on a visual display unit, of a multiped having a trunk and at least two legs depending therefrom, each leg including at least a first, upper part and a second, relatively lower part;
- (ii) to simulate the Newtonian forces that would be acting upon each separate part of the multiped at a given time and to apply these simulated forces to each said separate part so that, when displayed, each part moves under the influence of these simulated forces;
- (iii) to cause the image of each upper leg part to pivot about the trunk;
- (iv) to cause the image of the upper part of each leg to be moved via a simulated actuator in an arc relative to the said trunk;
- and
- (v) to cause the image of each relatively lower leg part to describe an apparently substantially free-swinging movement relative to its respective upper part;
- (vi) to provide a neural network having a plurality of neurones, the output of which neural network controls the actuator movement of each upper leg part such that the image of the multiped appears to walk.
A controller for a computer-generated image of a biped, the image comprising two legs depending from a trunk, each leg being actuated by a computer simulated actuator, the controller comprising a neural network having a plurality of neurones, the output of the neural network being arranged to control the computer simulated actuator such that the image of the trunk is caused to move as the image of the legs is moved.
A computer system comprising processing means arranged
- (i) to generate an image, on a visual display unit, of a biped having a trunk and legs depending therefrom, each leg including at least a first, upper part and a second, relatively lower part;
- (ii) to simulate the Newtonian forces that would be acting upon each separate part of the biped at a given time and to apply these simulated forces to each said separate part so that, when displayed, each part moves under the influence of these simulated forces;
- (iii) to cause the image of each upper leg part to pivot about the trunk;
- (iv) to provide a neural network having a plurality of neurones together arranged to act as two bi-directionally coupled pairs of identical oscillators;
- (v) to cause the image of the upper parts of each of the two legs to be moved by a force limited velocity constraint actuator, in an arc relative to the said trunk, the actuator being simulated by the processing means to calculate the simulated torque ΓT, at a time T, required to move the image of the upper part of its associated leg, under the effect of the said simulated Newtonian forces, as a function of the desired velocity of movement of the upper part of each leg relative to the body trunk, and wherein the desired velocity of movement is related to a difference between the actual and the desired angle between each upper leg part and the body trunk, the desired relative angle being derived from the neural network;
- and
- (vi) to cause the image of each lower leg part to describe an apparently substantially free-swinging movement relative to its respective upper part as the said upper part moves in its said arc;
- the output of the neural network being arranged to control the simulated actuator such that the image of the trunk is caused to move as the image of the legs is moved.
A computer program comprising program elements which, when executed on a digital computer, cause a processor thereof:
- (i) to generate an image, on a visual display unit, of a multiped having a trunk and at least two legs depending therefrom, each leg including at least a first, upper part and a second, relatively lower part;
- (ii) to simulate the Newtonian forces that would be acting upon each separate part of the multiped at a given time and to apply these simulated forces to each said separate part so that, when displayed, each part moves under the influence of these simulated forces;
- (iii) to cause the image of each upper leg part to pivot about the trunk;
- (iv) to provide a neural network having a plurality of neurones together arranged to act as two bi-directionally coupled pairs of identical oscillators;
- (v) to cause the image of the upper parts of each of the two legs to be moved by an actuator, in an arc relative to the said trunk;
- and
- (vi) to cause the image of each lower leg part to describe an apparently substantially free-swinging movement relative to its respective upper part as the said upper part moves in its said arc;
- the output of the neural network being arranged to control the simulated actuator such that the image of the trunk is caused to move as the image of the legs is moved.
A method of controlling the locomotion of a computer-generated biped, comprising the steps of:
- (a) establishing a neural network having a plurality of neurones;
- (b) generating a computer image of a body trunk and at least two legs, each leg depending from the trunk;
- (c) simulating the Newtonian forces that would be acting upon each separate part of the computer-generated object at a given time;
- (d) applying those simulated forces to each said separate part so that, when displayed on a visual display unit, each part appears to move under the influence of those simulated forces;
- (e) simulating an actuator for actuation of each said leg;
- and
- (f) controlling the operation of the actuator via an output from the neural network.
A method of optimizing the network parameters in a neural network controller for controlling the locomotion of a computer-generated image of a multiped, the method comprising:
- (i) generating a plurality of different trial arrays of network property values;
- (ii) applying the different trial arrays to the neural network to create different trial neural networks;
- (iii) identifying those arrays selected from the plurality of different arrays which, when applied to the neural networks, form trial neural networks which optimize the control of the said image of the multiped in accordance with at least the criterion that the distance, d, over which an end of the lower part of a rearmost leg of the computer-generated image should have travelled from the origin should be maximized;
- the method further comprising:
- aborting, as non-optimized, the consideration of those arrays forming trial neural networks when at least one of the following conditions is met:
- (a) a point attractor is reached such that the image when controlled by that trial network stops moving away from the origin,
- (b) the centre of mass or trunk of the multiped, as determined by applying Newtonian mechanics to the object, drops below a threshold height;
- and/or
- (c) the multiped does not move away from the origin and/or falls over prior to moving away therefrom.
A controller for control of cyclical movement of an appendage of an artificial or computer-simulated body, the controller comprising a neural network having a plurality of neurones together arranged to act as two bi-directionally coupled arrays of identical oscillators.
A computer system substantially as herein described with reference to and as illustrated in the accompanying drawings.
A controller for a computer-generated image substantially as herein described with reference to and as illustrated in the accompanying drawings.
A computer program substantially as herein described with reference to and as illustrated in the accompanying drawings.
A method of controlling the locomotion of a computer-generated multiped substantially as herein described with reference to and as illustrated in the accompanying drawings.
A method of optimizing the network parameters in a neural network controller substantially as herein described with reference to and as illustrated in the accompanying drawings.
Dependencies are inferred from the claim text.